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   <news:title>QT-Optによる視覚基盤ロボット把持の大規模強化学習（QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation）</news:title>
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   <news:title>独立深層学習行列解析による多チャンネル音源分離（Independent Deeply Learned Matrix Analysis for Multichannel Audio Source Separation）</news:title>
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   <news:title>非均一サンプリングからの行列補完（Matrix Completion from Non-Uniformly Sampled Entries）</news:title>
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    <news:language>ja</news:language>
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   <news:title>航空映像における主要物体の階層的深層共分割（Hierarchical Deep Co-segmentation of Primary Objects in Aerial Videos）</news:title>
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   <news:title>量子ランダム自己改変計算（Quantum Random Self-Modifiable Computation）</news:title>
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   <news:title>人の目に合うサリエンシー評価を学習する（Learning a Saliency Evaluation Metric Using Crowdsourced Perceptual Judgments）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Guided evolutionary strategiesの実務的解説（Guided evolutionary strategies: Augmenting random search with surrogate gradients）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>条件付きスパースℓp回帰の実務的含意（Conditional Sparse ℓp-norm Regression With Optimal Probability）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>核の短距離相関のエネルギー・運動量依存性（Energy and momentum dependence of nuclear short-range correlations - Spectral function, exclusive scattering experiments and the contact formalism）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>幼児向けウェブ学習プラットフォームの採用意図要因（The Determinants For User Intention To Adopt Web Based Early Childhood Supplementary Educational Platform）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>予算制約付きデュアルSVM訓練（Dual SVM Training on a Budget）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T20:29:39Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>遅延付き確率的勾配降下法の収束解析（A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T20:29:29Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Deep Feature Factorizationによる概念発見（Deep Feature Factorization For Concept Discovery）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T20:29:12Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>競合する隠れユニットによる教師なし学習（Unsupervised Learning by Competing Hidden Units）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T19:37:56Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>名前一致（Record Linkage）に基づく確率的手法による顧客名照合（Record Linkage to Match Customer Names: A Probabilistic Approach）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T19:37:39Z</lastmod>
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    <news:language>ja</news:language>
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   <news:title>事前計算された黄金分割探索によるBudgeted SGD-SVMの高速化（Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>マルチマージによる予算付きSGD-SVMの高速化（Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>生化学回路における確率的推論の具現化（Embodying probabilistic inference in biochemical circuits）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T19:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>セプシス患者のICU死亡リスク検出を高精度化する意味的強化動的ベイジアンネットワーク（Semantically Enhanced Dynamic Bayesian Network for Detecting Sepsis Mortality Risk in ICU Patients with Infection）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T19:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>データ適応型圧縮センシングの学習—勾配アンローリングによる測定行列の最適化（Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T19:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>モジュール化メタラーニングの原理と実践（Modular meta-learning）</news:title>
   <news:publication_date>2026-05-20T19:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/692403</loc>
  <lastmod>2026-05-20T18:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stripe 82 1–2 GHz VLAスナップショット調査の多波長カウンターパート解析（The Stripe 82 1–2 GHz Very Large Array Snapshot Survey: Multiwavelength Counterparts）</news:title>
   <news:publication_date>2026-05-20T18:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T18:44:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>疾患進行学習を活用した医療画像認識の刷新（Leveraging Disease Progression Learning for Medical Image Recognition）</news:title>
   <news:publication_date>2026-05-20T18:44:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692399</loc>
  <lastmod>2026-05-20T18:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>生波形で挑む音楽生成の課題（The challenge of realistic music generation: modelling raw audio at scale）</news:title>
   <news:publication_date>2026-05-20T18:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692397</loc>
  <lastmod>2026-05-20T18:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存の社会的慣習を観察データで学習する（Learning Existing Social Conventions via Observationally Augmented Self-Play）</news:title>
   <news:publication_date>2026-05-20T18:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-05-20T18:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>確率データベースにおける任意時点近似の一般枠組み（A General Framework for Anytime Approximation in Probabilistic Databases）</news:title>
   <news:publication_date>2026-05-20T18:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ランダムシャッフルは有限エポックでSGDを上回る（Random Shuffling Beats SGD after Finite Epochs）</news:title>
   <news:publication_date>2026-05-20T18:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-20T18:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作物収量予測のための効率的データウェアハウス（An Efficient Data Warehouse for Crop Yield Prediction）</news:title>
   <news:publication_date>2026-05-20T18:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692389</loc>
  <lastmod>2026-05-20T17:51:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep k-Meansによる表現学習とクラスタリングの同時最適化（Deep k-Means: Jointly clustering with k-Means and learning representations）</news:title>
   <news:publication_date>2026-05-20T17:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692387</loc>
  <lastmod>2026-05-20T17:50:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的シェーピングにおけるブラインド復号指標推定（Blind Decoding-Metric Estimation for Probabilistic Shaping via Expectation Maximization）</news:title>
   <news:publication_date>2026-05-20T17:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692385</loc>
  <lastmod>2026-05-20T17:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Blending Units（ADAPTIVE BLENDING UNITS: TRAINABLE ACTIVATION FUNCTIONS FOR DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-20T17:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692383</loc>
  <lastmod>2026-05-20T17:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆カウントの密度適応ネットワーク（Crowd Counting with Density Adaption Networks）</news:title>
   <news:publication_date>2026-05-20T17:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692381</loc>
  <lastmod>2026-05-20T17:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デイアクティック・イメージ・マッピングによる姿勢不変な操作学習（Deictic Image Mapping）</news:title>
   <news:publication_date>2026-05-20T17:49:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692379</loc>
  <lastmod>2026-05-20T17:49:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓ∞,1混合ノルム球への効率的な射影：ニュートン根探索法による高速化（Efficient Projection onto the ℓ∞,1 Mixed-Norm Ball using a Newton Root Search Method）</news:title>
   <news:publication_date>2026-05-20T17:49:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692377</loc>
  <lastmod>2026-05-20T17:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数は低次元か？（Is your function low-dimensional?）</news:title>
   <news:publication_date>2026-05-20T17:49:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692375</loc>
  <lastmod>2026-05-20T16:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号なしラプラシアンスペクトルで決定されるグラフの意義（Graphs determined by signless Laplacian Spectra）</news:title>
   <news:publication_date>2026-05-20T16:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692373</loc>
  <lastmod>2026-05-20T16:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題モデル学習のための敵対的能動探索（Adversarial Active Exploration for Inverse Dynamics Model Learning）</news:title>
   <news:publication_date>2026-05-20T16:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692371</loc>
  <lastmod>2026-05-20T16:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件性の原理が高次元回帰に与える示唆（The conditionality principle in high-dimensional regression）</news:title>
   <news:publication_date>2026-05-20T16:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692369</loc>
  <lastmod>2026-05-20T16:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるモチーフとニューロン集団検出（LEMONADE: Learned Motif and Neuronal Assembly Detection in Calcium Imaging Videos）</news:title>
   <news:publication_date>2026-05-20T16:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692367</loc>
  <lastmod>2026-05-20T16:56:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的指数型ファミリー因子分解モデルのための分離拡張カルマンフィルタ (The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models)</news:title>
   <news:publication_date>2026-05-20T16:56:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692365</loc>
  <lastmod>2026-05-20T16:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市民社会ラボ：市民サイエンス枠組みにおける人間行動実験のデジタルプラットフォーム（Citizen Social Lab: A digital platform for human behaviour experimentation within a citizen science framework）</news:title>
   <news:publication_date>2026-05-20T16:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692363</loc>
  <lastmod>2026-05-20T16:56:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>界面活性剤で覆われた変形滴の電気流体移動（Electrohydrodynamic migration of a surfactant-coated deformable drop in Poiseuielle flow）</news:title>
   <news:publication_date>2026-05-20T16:56:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692361</loc>
  <lastmod>2026-05-20T16:04:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数コントラストMRIのための連結辞書学習（Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction）</news:title>
   <news:publication_date>2026-05-20T16:04:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692359</loc>
  <lastmod>2026-05-20T16:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト非依存の話者認証で嵐を呼んだ組合せ手法（Text-Independent Speaker Verification Based on Deep Neural Networks and Segmental Dynamic Time Warping）</news:title>
   <news:publication_date>2026-05-20T16:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692357</loc>
  <lastmod>2026-05-20T16:03:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスを開く — データ駆動型の説明手法の要点（Open the Black Box: Data-Driven Explanation of Black Box Decision Systems）</news:title>
   <news:publication_date>2026-05-20T16:03:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692355</loc>
  <lastmod>2026-05-20T16:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autograd Image Registration Laboratory（AIRLab: Autograd Image Registration Laboratory）</news:title>
   <news:publication_date>2026-05-20T16:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692353</loc>
  <lastmod>2026-05-20T16:02:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的VampPriorを用いた変分公平オートエンコーダ（Hierarchical VampPrior Variational Fair Auto-Encoder）</news:title>
   <news:publication_date>2026-05-20T16:02:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692351</loc>
  <lastmod>2026-05-20T16:02:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接線空間正則化による動的システムのニューラルネットワークモデル改善（Tangent-Space Regularization for Neural-Network Models of Dynamical Systems）</news:title>
   <news:publication_date>2026-05-20T16:02:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692349</loc>
  <lastmod>2026-05-20T16:02:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体上の構造化予測（Manifold Structured Prediction）</news:title>
   <news:publication_date>2026-05-20T16:02:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692347</loc>
  <lastmod>2026-05-20T15:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化された自動音楽生成のための生波形生成モデルの条件付け（Conditioning Deep Generative Raw Audio Models for Structured Automatic Music）</news:title>
   <news:publication_date>2026-05-20T15:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692345</loc>
  <lastmod>2026-05-20T15:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分オートエンコーダを用いた金属結合タンパク質設計と新規フォールド創出（Design of metalloproteins and novel protein folds using variational autoencoders）</news:title>
   <news:publication_date>2026-05-20T15:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692343</loc>
  <lastmod>2026-05-20T15:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰問題におけるドロップアウトに基づく能動学習（Dropout-based Active Learning for Regression）</news:title>
   <news:publication_date>2026-05-20T15:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692341</loc>
  <lastmod>2026-05-20T15:09:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合辞書学習に基づくマルチモーダル画像ノイズ除去（MULTIMODAL IMAGE DENOISING BASED ON COUPLED DICTIONARY LEARNING）</news:title>
   <news:publication_date>2026-05-20T15:09:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692339</loc>
  <lastmod>2026-05-20T15:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化経路の復元解析とDeep Convolutional Sparse Coding（Analysing recovery of activation pathways in DCNNs via Deep Convolutional Sparse Coding）</news:title>
   <news:publication_date>2026-05-20T15:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692337</loc>
  <lastmod>2026-05-20T15:08:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル画像処理のための結合辞書学習（MULTI-MODAL IMAGE PROCESSING BASED ON COUPLED DICTIONARY LEARNING）</news:title>
   <news:publication_date>2026-05-20T15:08:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692335</loc>
  <lastmod>2026-05-20T15:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運用的宇宙天気予報におけるアンサンブル手法の重要性（The importance of ensemble techniques for operational space weather forecasting）</news:title>
   <news:publication_date>2026-05-20T15:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692333</loc>
  <lastmod>2026-05-20T14:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹部脂肪組織の自動セグメンテーションに関する全畳み込みネットワークの応用（Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI）</news:title>
   <news:publication_date>2026-05-20T14:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692331</loc>
  <lastmod>2026-05-20T14:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph-to-Sequence学習とGGNNによる構造表現の活用（Graph-to-Sequence Learning using Gated Graph Neural Networks）</news:title>
   <news:publication_date>2026-05-20T14:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692329</loc>
  <lastmod>2026-05-20T14:16:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次分解可能サブモジュラ関数の最小化（Quadratic Decomposable Submodular Function Minimization）</news:title>
   <news:publication_date>2026-05-20T14:16:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692327</loc>
  <lastmod>2026-05-20T14:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文埋め込みの改良をもたらす一般化プーリング手法（Enhancing Sentence Embedding with Generalized Pooling）</news:title>
   <news:publication_date>2026-05-20T14:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692325</loc>
  <lastmod>2026-05-20T14:16:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SuperPCAによる超高分解能画像の領域別次元削減（SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery）</news:title>
   <news:publication_date>2026-05-20T14:16:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692323</loc>
  <lastmod>2026-05-20T14:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における近似最近傍探索（Approximate Nearest Neighbor Search in High Dimensions）</news:title>
   <news:publication_date>2026-05-20T14:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692321</loc>
  <lastmod>2026-05-20T14:14:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段落認識型トピックモデルによる文書の意味構造の解明（Unveiling the semantic structure of text documents using paragraph-aware Topic Models）</news:title>
   <news:publication_date>2026-05-20T14:14:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692319</loc>
  <lastmod>2026-05-20T13:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多人数の逆強化学習が一般和ゲームに挑む（Multi-agent Inverse Reinforcement Learning for Certain General-Sum Stochastic Games）</news:title>
   <news:publication_date>2026-05-20T13:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692317</loc>
  <lastmod>2026-05-20T13:23:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-20T13:23:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692315</loc>
  <lastmod>2026-05-20T13:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療関係抽出のハイブリッド深層学習法（A Hybrid Deep Learning Approach for Medical Relation Extraction）</news:title>
   <news:publication_date>2026-05-20T13:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692313</loc>
  <lastmod>2026-05-20T13:22:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的アンサンブルによる協調フィルタ（Probabilistic Ensemble of Collaborative Filters）</news:title>
   <news:publication_date>2026-05-20T13:22:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692311</loc>
  <lastmod>2026-05-20T13:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル中国詩生成モデル（A Multi-Modal Chinese Poetry Generation Model）</news:title>
   <news:publication_date>2026-05-20T13:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692309</loc>
  <lastmod>2026-05-20T13:21:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>免疫系に学ぶ分散型・実体化された行動進化選択アルゴリズム（On an Immuno-inspired Distributed, Embodied Action-Evolution cum Selection Algorithm）</news:title>
   <news:publication_date>2026-05-20T13:21:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692307</loc>
  <lastmod>2026-05-20T13:21:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関したソフトウェア指標を自動緩和するAutoSpearman（AutoSpearman: Automatically Mitigating Correlated Software Metrics for Interpreting Defect Models）</news:title>
   <news:publication_date>2026-05-20T13:21:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692297</loc>
  <lastmod>2026-05-20T12:30:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dropoutを最適化トリックとして理解する（Understanding Dropout as an Optimization Trick）</news:title>
   <news:publication_date>2026-05-20T12:30:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692295</loc>
  <lastmod>2026-05-20T12:30:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関疑似周辺メトロポリス・ヘイスティングと準ニュートン提案（Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals）</news:title>
   <news:publication_date>2026-05-20T12:30:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692293</loc>
  <lastmod>2026-05-20T12:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数値データのセマンティックラベリングを深層距離学習で解く（EmbNum: Semantic Labeling for Numerical Values with Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-20T12:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692291</loc>
  <lastmod>2026-05-20T12:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な知識制約を持つ深層生成モデル（Deep Generative Models with Learnable Knowledge Constraints）</news:title>
   <news:publication_date>2026-05-20T12:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692289</loc>
  <lastmod>2026-05-20T12:29:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Q-DeckRecによる高速デッキ推薦システム (Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games)</news:title>
   <news:publication_date>2026-05-20T12:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692287</loc>
  <lastmod>2026-05-20T12:29:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドロップアウトが生む暗黙的バイアス（On the Implicit Bias of Dropout）</news:title>
   <news:publication_date>2026-05-20T12:29:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692285</loc>
  <lastmod>2026-05-20T12:28:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置を跨いだ行動認識のための分層転移学習（Cross-position Activity Recognition with Stratified Transfer Learning）</news:title>
   <news:publication_date>2026-05-20T12:28:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692283</loc>
  <lastmod>2026-05-20T11:37:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルチルTiO2における急速重イオン軌跡の微細構造（Fine structure of swift heavy ion track in rutile TiO2）</news:title>
   <news:publication_date>2026-05-20T11:37:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692281</loc>
  <lastmod>2026-05-20T11:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Boulevardによる正則化確率的勾配ブースティング木とその極限分布 (Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution)</news:title>
   <news:publication_date>2026-05-20T11:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692279</loc>
  <lastmod>2026-05-20T11:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄なエンティティ抽出のための実践的逐次学習フレームワーク (A Practical Incremental Learning Framework For Sparse Entity Extraction)</news:title>
   <news:publication_date>2026-05-20T11:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692277</loc>
  <lastmod>2026-05-20T11:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>REST-ler：REST API自動テストの知能化（REST-ler: Automatic Intelligent REST API Fuzzing）</news:title>
   <news:publication_date>2026-05-20T11:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692275</loc>
  <lastmod>2026-05-20T11:35:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保険クレームの計算的分析：GEICOケーススタディ（Computational Analysis of Insurance Complaints: GEICO Case Study）</news:title>
   <news:publication_date>2026-05-20T11:35:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692273</loc>
  <lastmod>2026-05-20T11:35:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床的に活用可能な遺伝子変異の多視点アンサンブル分類モデル（A Multi-View Ensemble Classification Model for Clinically Actionable Genetic Mutations）</news:title>
   <news:publication_date>2026-05-20T11:35:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692271</loc>
  <lastmod>2026-05-20T11:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-20T11:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692269</loc>
  <lastmod>2026-05-20T10:44:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUネットワークの可逆性と堅牢性の解析（Analysis of Invariance and Robustness via Invertibility of ReLU-Networks）</news:title>
   <news:publication_date>2026-05-20T10:44:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692267</loc>
  <lastmod>2026-05-20T10:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ディープラーニングの普遍的学習アルゴリズム（A Universal Training Algorithm for Quantum Deep Learning）</news:title>
   <news:publication_date>2026-05-20T10:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692265</loc>
  <lastmod>2026-05-20T10:43:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Request-and-Reverify: 高コストラベル下での概念ドリフト検出（Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels）</news:title>
   <news:publication_date>2026-05-20T10:43:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692263</loc>
  <lastmod>2026-05-20T10:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Identity Regression Space による人物再識別の新展開（Person Re-Identification in Identity Regression Space）</news:title>
   <news:publication_date>2026-05-20T10:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692261</loc>
  <lastmod>2026-05-20T10:43:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き独立性検定の新たな設計：Mimic and Classify（Mimic and Classify : A meta-algorithm for Conditional Independence Testing）</news:title>
   <news:publication_date>2026-05-20T10:43:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692259</loc>
  <lastmod>2026-05-20T10:42:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習における解釈性の重要性（Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory）</news:title>
   <news:publication_date>2026-05-20T10:42:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692257</loc>
  <lastmod>2026-05-20T10:42:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混雑環境における物理ベースのシーン推論による物体姿勢推定（Physics-based Scene-level Reasoning for Object Pose Estimation in Clutter）</news:title>
   <news:publication_date>2026-05-20T10:42:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692255</loc>
  <lastmod>2026-05-20T09:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RCTの結果を現実集団に翻訳する成果モデルアプローチ（An Outcome Model Approach to Translating a Randomized Controlled Trial Results to a Target Population）</news:title>
   <news:publication_date>2026-05-20T09:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692253</loc>
  <lastmod>2026-05-20T09:51:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分情報から線形関数を学ぶ手法と量子計算への応用（On learning linear functions from subset and its applications in quantum computing）</news:title>
   <news:publication_date>2026-05-20T09:51:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692251</loc>
  <lastmod>2026-05-20T09:51:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動できることを先に学ぶ（LEARNING WHAT YOU CAN DO BEFORE DOING ANYTHING）</news:title>
   <news:publication_date>2026-05-20T09:51:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692249</loc>
  <lastmod>2026-05-20T09:50:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DCA-Like とその加速版が拓く可視化最適化の高速化（A DCA-Like Algorithm and its Accelerated Version with Application in Data Visualization）</news:title>
   <news:publication_date>2026-05-20T09:50:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692247</loc>
  <lastmod>2026-05-20T09:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的自然勾配降下法が関数空間でベイズ後方分布を描く（Stochastic natural gradient descent draws posterior samples in function space）</news:title>
   <news:publication_date>2026-05-20T09:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692245</loc>
  <lastmod>2026-05-20T09:50:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRI画像の参照不要な自動画質評価を可能にする機械学習フレームワーク（A Machine-learning Framework for Automatic Reference-free Quality Assessment in MRI）</news:title>
   <news:publication_date>2026-05-20T09:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692243</loc>
  <lastmod>2026-05-20T09:50:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>「Behemoth」で読み解くエルゴード性とランダム行列理論（Eigenstate Thermalization, Random Matrix Theory and Behemoths）</news:title>
   <news:publication_date>2026-05-20T09:50:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692241</loc>
  <lastmod>2026-05-20T08:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイク付きウィグナー行列における検出の基本限界（Fundamental limits of detection in the spiked Wigner model）</news:title>
   <news:publication_date>2026-05-20T08:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692239</loc>
  <lastmod>2026-05-20T08:58:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-20T08:58:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>フレーム単位の楽器認識：音色とピッチによる解析（Frame-level Instrument Recognition by Timbre and Pitch）</news:title>
   <news:publication_date>2026-05-20T08:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692235</loc>
  <lastmod>2026-05-20T08:58:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的最尤推定の漸近特性（Asymptotic Properties of Recursive Maximum Likelihood Estimation in Non-Linear State-Space Models）</news:title>
   <news:publication_date>2026-05-20T08:58:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692233</loc>
  <lastmod>2026-05-20T08:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Prelude: SDN導入が引き起こす経路ループ検出とプライバシー保護（Prelude: Ensuring Inter-Domain Loop-Freedom in SDN-Enabled Networks）</news:title>
   <news:publication_date>2026-05-20T08:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692231</loc>
  <lastmod>2026-05-20T08:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画から自動生成する一枚画像深度学習（Learning Single-Image Depth from Videos using Quality Assessment Networks）</news:title>
   <news:publication_date>2026-05-20T08:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692229</loc>
  <lastmod>2026-05-20T08:57:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加速度データからのオンライン心拍推定（Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable）</news:title>
   <news:publication_date>2026-05-20T08:57:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692227</loc>
  <lastmod>2026-05-20T08:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子確率近似EMによる動的システム学習（Learning Dynamical Systems with Particle Stochastic Approximation EM）</news:title>
   <news:publication_date>2026-05-20T08:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692225</loc>
  <lastmod>2026-05-20T07:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低光子数位相回復におけるディープラーニングの活用（Low Photon Count Phase Retrieval Using Deep Learning）</news:title>
   <news:publication_date>2026-05-20T07:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692223</loc>
  <lastmod>2026-05-20T07:57:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Inference Treesによる適応的推論と探索（Inference Trees: Adaptive Inference with Exploration）</news:title>
   <news:publication_date>2026-05-20T07:57:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692221</loc>
  <lastmod>2026-05-20T07:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夜間環境認識を高める熱画像から可視画像への翻訳（IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation）</news:title>
   <news:publication_date>2026-05-20T07:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692219</loc>
  <lastmod>2026-05-20T07:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平行深層学習の限界突破（Pushing the boundaries of parallel Deep Learning – A practical approach）</news:title>
   <news:publication_date>2026-05-20T07:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692217</loc>
  <lastmod>2026-05-20T07:55:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の順序を伴う二変量単調行列の最適推定に向けて (Towards Optimal Estimation of Bivariate Isotonic Matrices with Unknown Permutations)</news:title>
   <news:publication_date>2026-05-20T07:55:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692215</loc>
  <lastmod>2026-05-20T07:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門医用語と消費者言語を埋め込み整合でつなぐ（Mapping Unparalleled Clinical Professional and Consumer Languages with Embedding Alignment）</news:title>
   <news:publication_date>2026-05-20T07:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692213</loc>
  <lastmod>2026-05-20T07:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変セグメンテーションのためのSkinNet（SkinNet: A Deep Learning Framework for Skin Lesion Segmentation）</news:title>
   <news:publication_date>2026-05-20T07:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692211</loc>
  <lastmod>2026-05-20T07:03:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼内視鏡における密な深度推定の自己教師あり学習（Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy）</news:title>
   <news:publication_date>2026-05-20T07:03:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692209</loc>
  <lastmod>2026-05-20T07:03:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変形物体操作のための学習ベースフィードバックコントローラ（Learning-based Feedback Controller for Deformable Object Manipulation）</news:title>
   <news:publication_date>2026-05-20T07:03:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692207</loc>
  <lastmod>2026-05-20T07:03:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気サイクルの感度に関するグローバルシミュレーション研究の示唆（ON THE SENSITIVITY OF MAGNETIC CYCLES IN GLOBAL SIMULATIONS OF SOLAR-LIKE STARS）</news:title>
   <news:publication_date>2026-05-20T07:03:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692205</loc>
  <lastmod>2026-05-20T07:02:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理モデルをデータから“写す”条件付き敵対的オートエンコーダによる音響クローン作成（Sounderfeit: Cloning a Physical Model using a Conditional Adversarial Autoencoder）</news:title>
   <news:publication_date>2026-05-20T07:02:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692203</loc>
  <lastmod>2026-05-20T07:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像における半自動RECISTラベリング（Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-20T07:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692201</loc>
  <lastmod>2026-05-20T07:02:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変的離散化によるパス積分の構築（Building a path-integral calculus: a covariant discretization approach）</news:title>
   <news:publication_date>2026-05-20T07:02:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692199</loc>
  <lastmod>2026-05-20T06:11:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ補間は統計的最適性と矛盾するか（Does data interpolation contradict statistical optimality?）</news:title>
   <news:publication_date>2026-05-20T06:11:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692197</loc>
  <lastmod>2026-05-20T06:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習の概観：連続制御の視点（A Tour of Reinforcement Learning: The View from Continuous Control）</news:title>
   <news:publication_date>2026-05-20T06:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692195</loc>
  <lastmod>2026-05-20T06:10:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交差点における文脈依存歩行者動作予測（Context-Aware Pedestrian Motion Prediction In Urban Intersections）</news:title>
   <news:publication_date>2026-05-20T06:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692193</loc>
  <lastmod>2026-05-20T06:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空レーザー測量データによる森林属性推定のためのガウス過程回帰（Gaussian Process Regression for Forest Attribute Estimation from Airborne Laser Scanning Data）</news:title>
   <news:publication_date>2026-05-20T06:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692191</loc>
  <lastmod>2026-05-20T06:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>tanh関数を通じた不確実性伝播とリザバーコンピューティングへの応用 (Propagating Uncertainty through the tanh Function with Application to Reservoir Computing)</news:title>
   <news:publication_date>2026-05-20T06:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692189</loc>
  <lastmod>2026-05-20T06:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型遅延耐性近接勾配アルゴリズムの実用的意味（A distributed flexible delay-tolerant proximal gradient algorithm）</news:title>
   <news:publication_date>2026-05-20T06:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692187</loc>
  <lastmod>2026-05-20T06:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差点で移動する歩行者の行動を場所を超えて予測する手法（A Transferable Pedestrian Motion Prediction Model for Intersections with Different Geometries）</news:title>
   <news:publication_date>2026-05-20T06:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692185</loc>
  <lastmod>2026-05-20T05:16:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異なType II超新星iPTF14hlsの後期観測（Late-time observations of the extraordinary Type II supernova iPTF14hls）</news:title>
   <news:publication_date>2026-05-20T05:16:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692183</loc>
  <lastmod>2026-05-20T05:16:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度を変えるカリキュラムで学習効率を上げる方法（Accuracy-based Curriculum Learning in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-20T05:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692181</loc>
  <lastmod>2026-05-20T05:15:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学的妥当な意思決定層を備えた時間的ニューラルネットワークによる物体認識（A temporal neural network model for object recognition using a biologically plausible decision making layer）</news:title>
   <news:publication_date>2026-05-20T05:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692179</loc>
  <lastmod>2026-05-20T05:15:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実信号上でのICA尤度最適化の高速化（Accelerating likelihood optimization for ICA on real signals）</news:title>
   <news:publication_date>2026-05-20T05:15:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692177</loc>
  <lastmod>2026-05-20T05:14:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし学習で監督あり法に迫る分類器の可能性（An Unsupervised Learning Classifier with Competitive Error Performance）</news:title>
   <news:publication_date>2026-05-20T05:14:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692175</loc>
  <lastmod>2026-05-20T05:14:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース報酬問題に対するデータ効率的な探索手法（Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards）</news:title>
   <news:publication_date>2026-05-20T05:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692173</loc>
  <lastmod>2026-05-20T04:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一チャネル音声の残響除去にGANを用いる手法（Single-channel Speech Dereverberation via Generative Adversarial Training）</news:title>
   <news:publication_date>2026-05-20T04:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692171</loc>
  <lastmod>2026-05-20T04:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線科医レベルの胸部X線自動診断システム（Towards Radiologist-Level Accurate Deep Learning System for Pulmonary Screening）</news:title>
   <news:publication_date>2026-05-20T04:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692169</loc>
  <lastmod>2026-05-20T04:22:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし音声活動検出のための堅牢な特徴クラスタリング（Robust Feature Clustering for Unsupervised Speech Activity Detection）</news:title>
   <news:publication_date>2026-05-20T04:22:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692167</loc>
  <lastmod>2026-05-20T04:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバル不変性を組み込んだ最適輸送（Towards Optimal Transport with Global Invariances）</news:title>
   <news:publication_date>2026-05-20T04:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692165</loc>
  <lastmod>2026-05-20T04:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道具操作のためのタスク指向把持学習（Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision）</news:title>
   <news:publication_date>2026-05-20T04:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692163</loc>
  <lastmod>2026-05-20T04:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学オートエンコーダの潜在空間と分子生成の多様性向上（Improving Chemical Autoencoder Latent Space and Molecular De-novo Generation Diversity with Heteroencoders）</news:title>
   <news:publication_date>2026-05-20T04:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692161</loc>
  <lastmod>2026-05-20T04:21:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車両再識別のための領域認識深層モデル（RAM: A REGION-AWARE DEEP MODEL FOR VEHICLE RE-IDENTIFICATION）</news:title>
   <news:publication_date>2026-05-20T04:21:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692159</loc>
  <lastmod>2026-05-20T03:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴マップの再重み付けによる色恒常性（Color Constancy by Reweighting Image Feature Maps）</news:title>
   <news:publication_date>2026-05-20T03:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692157</loc>
  <lastmod>2026-05-20T03:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Track Xplorerによるセンサーデータ分類の可視化と解析（Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions）</news:title>
   <news:publication_date>2026-05-20T03:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692155</loc>
  <lastmod>2026-05-20T03:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレシーズン作物収量予測のためのスケーラブルな機械学習システム（A Scalable Machine Learning System for Pre-Season Agriculture Yield Forecast）</news:title>
   <news:publication_date>2026-05-20T03:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692153</loc>
  <lastmod>2026-05-20T03:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面上の完全フーリエ空間クレブシュ–ゴルダンネット（Clebsch–Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-20T03:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692151</loc>
  <lastmod>2026-05-20T03:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワーク圧縮のためのDeep k-Means（Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions）</news:title>
   <news:publication_date>2026-05-20T03:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692149</loc>
  <lastmod>2026-05-20T03:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの訓練挙動の理解と正則化の改善（Towards a Better Understanding and Regularization of GAN Training Dynamics）</news:title>
   <news:publication_date>2026-05-20T03:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692147</loc>
  <lastmod>2026-05-20T03:29:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FBI-Poseが切り拓く2D画像と3D人体姿勢推定の橋渡し（FBI-Pose: Towards Bridging the Gap between 2D Images and 3D Human Poses using Forward-or-Backward Information）</news:title>
   <news:publication_date>2026-05-20T03:29:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692145</loc>
  <lastmod>2026-05-20T02:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視学習における金融的影響の均衡化（Equalizing Financial Impact in Supervised Learning）</news:title>
   <news:publication_date>2026-05-20T02:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692143</loc>
  <lastmod>2026-05-20T02:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注目機構を用いた少数ショット人物再識別のメタ学習（Attention-based Few-Shot Person Re-identification Using Meta Learning）</news:title>
   <news:publication_date>2026-05-20T02:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692141</loc>
  <lastmod>2026-05-20T02:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>N-Gram Graphによる分子表現の単純化と有効性（N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules）</news:title>
   <news:publication_date>2026-05-20T02:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692139</loc>
  <lastmod>2026-05-20T02:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Power Normalizationsによる深層プーリングの再考（A Deeper Look at Power Normalizations）</news:title>
   <news:publication_date>2026-05-20T02:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692137</loc>
  <lastmod>2026-05-20T02:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフーリエ特徴量の統一的解析への試み (Towards a Unified Analysis of Random Fourier Features)</news:title>
   <news:publication_date>2026-05-20T02:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692135</loc>
  <lastmod>2026-05-20T02:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Thompson Samplingの差分プライバシー性と実務的含意（On The Differential Privacy of Thompson Sampling With Gaussian Prior）</news:title>
   <news:publication_date>2026-05-20T02:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692133</loc>
  <lastmod>2026-05-20T02:37:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動作キャプチャの自動セグメンテーションを高速化する時系列畳み込み網（Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data）</news:title>
   <news:publication_date>2026-05-20T02:37:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692131</loc>
  <lastmod>2026-05-20T01:46:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合ネットワークとランダム化ニューラルネットワークの統合によるテクスチャ解析（FUSION OF COMPLEX NETWORKS AND RANDOMIZED NEURAL NETWORKS FOR TEXTURE ANALYSIS）</news:title>
   <news:publication_date>2026-05-20T01:46:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692129</loc>
  <lastmod>2026-05-20T01:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SSIMLayerによる堅牢な表現学習の提案（SSIMLayer: Towards Robust Deep Representation Learning via Nonlinear Structural Similarity）</news:title>
   <news:publication_date>2026-05-20T01:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692127</loc>
  <lastmod>2026-05-20T01:46:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自転車利用者の経路選好を疎な軌跡から推定する手法（INFERRING ROUTING PREFERENCES OF BICYCLISTS FROM SPARSE SETS OF TRAJECTORIES）</news:title>
   <news:publication_date>2026-05-20T01:46:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692125</loc>
  <lastmod>2026-05-20T01:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模MIMOのチャネル推定を深層ニューラルネットで高速化する手法（Channel Estimation for Massive MIMO Communication System Using Deep Neural Network）</news:title>
   <news:publication_date>2026-05-20T01:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692123</loc>
  <lastmod>2026-05-20T01:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲートパターン量子デバイスにおける静電境界条件の実験的検証（Experimental verification of electrostatic boundary conditions in gate-patterned quantum devices）</news:title>
   <news:publication_date>2026-05-20T01:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692121</loc>
  <lastmod>2026-05-20T01:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ構造学習から作る深層ニューラルネットワーク（Constructing Deep Neural Networks by Bayesian Network Structure Learning）</news:title>
   <news:publication_date>2026-05-20T01:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692119</loc>
  <lastmod>2026-05-20T01:45:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フレーバー依存のEMC効果（Flavor-dependent EMC effect from a nucleon swelling model）</news:title>
   <news:publication_date>2026-05-20T01:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692117</loc>
  <lastmod>2026-05-20T00:54:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブワード強化埋め込みによるクローズ読解の精度向上（Subword-augmented Embedding for Cloze Reading Comprehension）</news:title>
   <news:publication_date>2026-05-20T00:54:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692115</loc>
  <lastmod>2026-05-20T00:53:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話の文脈を精緻化する深層発話集約（Modeling Multi-turn Conversation with Deep Utterance Aggregation）</news:title>
   <news:publication_date>2026-05-20T00:53:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692113</loc>
  <lastmod>2026-05-20T00:53:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAGE光度天文サーベイの技術的解説（The SAGE Photometric Sky Survey: Technical Description）</news:title>
   <news:publication_date>2026-05-20T00:53:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692111</loc>
  <lastmod>2026-05-20T00:53:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像の超解像を実現する3D畳み込みニューラルネットワーク（CT-image Super Resolution Using 3D Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-20T00:53:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692109</loc>
  <lastmod>2026-05-20T00:53:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3DボディスケルトンにおけるCNNベースの動作認識と教師ありドメイン適応（CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps）</news:title>
   <news:publication_date>2026-05-20T00:53:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692107</loc>
  <lastmod>2026-05-20T00:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン署名検証における深層表現による新しい記述子（Online Signature Verification using Deep Representation: A new Descriptor）</news:title>
   <news:publication_date>2026-05-20T00:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692105</loc>
  <lastmod>2026-05-20T00:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックプロパゲーションを超えて：補助変数によるオンライン交互最小化（Beyond Backprop: Online Alternating Minimization with Auxiliary Variables）</news:title>
   <news:publication_date>2026-05-20T00:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692103</loc>
  <lastmod>2026-05-20T00:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きケンドールのタウを分類視点で捉える（A classification point-of-view about conditional Kendall’s tau）</news:title>
   <news:publication_date>2026-05-20T00:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692101</loc>
  <lastmod>2026-05-19T23:52:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物の姿勢を別人に移す生成モデルの可能性（Generative Models for Pose Transfer）</news:title>
   <news:publication_date>2026-05-19T23:52:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692099</loc>
  <lastmod>2026-05-19T23:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LinkedIn SalaryにおけるCompany2vecとベイズ平滑化の実装（How LinkedIn Economic Graph Bonds Information and Product: Applications in LinkedIn Salary）</news:title>
   <news:publication_date>2026-05-19T23:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692097</loc>
  <lastmod>2026-05-19T23:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多面性と欠損を扱う表現学習の切り札（Disentangled VAE Representations for Multi-Aspect and Missing Data）</news:title>
   <news:publication_date>2026-05-19T23:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692095</loc>
  <lastmod>2026-05-19T23:51:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T23:51:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T23:50:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T23:50:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-19T22:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Parallel Transport Unfolding（Parallel Transport Unfolding: A Connection-based Manifold Learning Approach）</news:title>
   <news:publication_date>2026-05-19T22:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692087</loc>
  <lastmod>2026-05-19T22:59:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T22:59:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692085</loc>
  <lastmod>2026-05-19T22:59:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入門物理でのプログラミング演習のハイブリッド手法（A Hybrid Approach for Using Programming Exercises in Introductory Physics）</news:title>
   <news:publication_date>2026-05-19T22:59:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692083</loc>
  <lastmod>2026-05-19T22:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T22:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692081</loc>
  <lastmod>2026-05-19T22:58:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルウェア分類器を敵対的摂動から守る重み非負制約の考え方（Defending Malware Classification Networks Against Adversarial Perturbations with Non-Negative Weight Restrictions）</news:title>
   <news:publication_date>2026-05-19T22:58:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692079</loc>
  <lastmod>2026-05-19T22:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆の知恵の最適化（Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching）</news:title>
   <news:publication_date>2026-05-19T22:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692077</loc>
  <lastmod>2026-05-19T22:58:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字レベルニューラル機械翻訳に対する敵対的事例の研究（On Adversarial Examples for Character-Level Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-19T22:58:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692075</loc>
  <lastmod>2026-05-19T22:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>筆画ベースの文字再構成（Stroke-based Character Reconstruction）</news:title>
   <news:publication_date>2026-05-19T22:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692073</loc>
  <lastmod>2026-05-19T22:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的スペクトルマッチングとワンショット学習（Dynamic Spectrum Matching with One-shot Learning）</news:title>
   <news:publication_date>2026-05-19T22:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692071</loc>
  <lastmod>2026-05-19T22:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間赤外過剰銀河の実像とIR/UV星形成率比較（THE MOSDEF SURVEY: THE NATURE OF MID-INFRARED EXCESS GALAXIES AND A COMPARISON OF IR AND UV STAR FORMATION TRACERS AT z ∼2）</news:title>
   <news:publication_date>2026-05-19T22:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T22:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラップされた少数体系を撮像するための量子点広がり関数（Quantum point spread function for imaging trapped few-body systems with a quantum gas microscope）</news:title>
   <news:publication_date>2026-05-19T22:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692067</loc>
  <lastmod>2026-05-19T22:05:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準秩序化イオンビームを用いた電子−イオンコライダーの可能性（Electron-Ion Collider with Quasi-Ordered Ion Beam）</news:title>
   <news:publication_date>2026-05-19T22:05:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能なコーデ推薦：アウトフィット照合とコメント生成の同時学習（Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation）</news:title>
   <news:publication_date>2026-05-19T22:05:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T22:04:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理知識を組み込んだガウス過程回帰による電力網の短期予測と不確実性推定（Physics-informed Machine Learning Method for Forecasting and Uncertainty Quantiﬁcation of Partially Observed and Unobserved States in Power Grids）</news:title>
   <news:publication_date>2026-05-19T22:04:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T21:14:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692059</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>企業向け脅威管理のための再帰的PLSアプローチ（A Recursive PLS based Approach for Enterprise Threat Management）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692057</loc>
  <lastmod>2026-05-19T21:13:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー最適化ロボットアーム経路計画（Energy Optimized Robot Arm Path Planning using Differential Evolution in Dynamic Environment）</news:title>
   <news:publication_date>2026-05-19T21:13:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692055</loc>
  <lastmod>2026-05-19T21:12:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑モデルを可視化する統一インターフェース（DALEX: Explainers for Complex Predictive Models in R）</news:title>
   <news:publication_date>2026-05-19T21:12:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692053</loc>
  <lastmod>2026-05-19T21:12:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いた合成乱流入口生成器（Synthetic turbulent inflow generator using machine learning）</news:title>
   <news:publication_date>2026-05-19T21:12:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692051</loc>
  <lastmod>2026-05-19T21:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T21:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692049</loc>
  <lastmod>2026-05-19T21:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索順位操作の不正の匿名解除（Search Rank Fraud De-Anonymization in Online Systems）</news:title>
   <news:publication_date>2026-05-19T21:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692047</loc>
  <lastmod>2026-05-19T20:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習の概説（Deep Reinforcement Learning: An Overview）</news:title>
   <news:publication_date>2026-05-19T20:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692045</loc>
  <lastmod>2026-05-19T20:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース・マニフォールド変換の本質（The Sparse Manifold Transform）</news:title>
   <news:publication_date>2026-05-19T20:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692043</loc>
  <lastmod>2026-05-19T20:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T20:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692041</loc>
  <lastmod>2026-05-19T20:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T20:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692039</loc>
  <lastmod>2026-05-19T20:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>xGEMsによるブラックボックス説明の新展開（xGEMs: Generating Examplars to Explain Black-Box Models）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692037</loc>
  <lastmod>2026-05-19T20:18:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep SNPによるSNPアレイデータのブレークポイント検出（Deep SNP: An End-to-end Deep Neural Network for Break-point Detection in SNP Array Genomic Data）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692035</loc>
  <lastmod>2026-05-19T20:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜層の自動分割を深層学習で完結させる一手（A deep learning framework for segmentation of retinal layers from OCT images）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692033</loc>
  <lastmod>2026-05-19T19:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の拡散スキャッタリング変換（Diffusion Scattering Transforms on Graphs）</news:title>
   <news:publication_date>2026-05-19T19:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692031</loc>
  <lastmod>2026-05-19T19:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692029</loc>
  <lastmod>2026-05-19T19:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートインバータによる系統プロービングで負荷を学習する：第II部 – プロービング注入設計 (Smart Inverter Grid Probing for Learning Loads: Part II – Probing Injection Design)</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692027</loc>
  <lastmod>2026-05-19T19:17:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>急性呼吸器感染症予測のドメイン適応（Domain Adaptation for Acute Respiratory Infection Prediction）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T19:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多目的（Many-Goals）強化学習の拡張と実用性（Many-Goals Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T19:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-19T19:16:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートインバータによるグリッドプロービングで負荷を学ぶ（Smart Inverter Grid Probing for Learning Loads: Part I – Identifiability Analysis）</news:title>
   <news:publication_date>2026-05-19T19:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692019</loc>
  <lastmod>2026-05-19T18:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河周縁ガスの一貫性スケール（The Coherence Scale of the Cool Circumgalactic Medium）</news:title>
   <news:publication_date>2026-05-19T18:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692017</loc>
  <lastmod>2026-05-19T18:24:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ランダムウォークのPCA解析（PCA of high dimensional random walks with comparison to neural network training）</news:title>
   <news:publication_date>2026-05-19T18:24:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692015</loc>
  <lastmod>2026-05-19T18:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的グラフ表現学習と微分可能なプーリング（Hierarchical Graph Representation Learning with Differentiable Pooling）</news:title>
   <news:publication_date>2026-05-19T18:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692013</loc>
  <lastmod>2026-05-19T18:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散逸系における量子電流（Quantum current in dissipative systems）</news:title>
   <news:publication_date>2026-05-19T18:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692011</loc>
  <lastmod>2026-05-19T18:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ネスト分散還元による局所最小解探索（Finding Local Minima via Stochastic Nested Variance Reduction）</news:title>
   <news:publication_date>2026-05-19T18:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692009</loc>
  <lastmod>2026-05-19T18:23:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子コードをニューラルネットワークで表現する（Quantum Codes from Neural Networks）</news:title>
   <news:publication_date>2026-05-19T18:23:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692007</loc>
  <lastmod>2026-05-19T18:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOODS-N フィールドにおける z ∼2.5–3 のイオン化源探索の意義（z ∼2.5–3 Ionizers in the GOODS-N Field）</news:title>
   <news:publication_date>2026-05-19T18:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692005</loc>
  <lastmod>2026-05-19T17:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン知識と深層学習の組合せによる感情分析（Combination of Domain Knowledge and Deep Learning for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-19T17:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692003</loc>
  <lastmod>2026-05-19T17:31:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム場を用いた交通流動学習（Learning Traffic Flow Dynamics using Random Fields）</news:title>
   <news:publication_date>2026-05-19T17:31:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692001</loc>
  <lastmod>2026-05-19T17:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dense Object Netsによるロボット操作のための密な視覚記述子学習（Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation）</news:title>
   <news:publication_date>2026-05-19T17:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691999</loc>
  <lastmod>2026-05-19T17:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模化したSLICアルゴリズムによる高速化と汎用化の実装（Scalable Simple Linear Iterative Clustering）</news:title>
   <news:publication_date>2026-05-19T17:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691997</loc>
  <lastmod>2026-05-19T17:29:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESO telbib：経験から学び未来に備える（ESO telbib: learning from experience, preparing for the future）</news:title>
   <news:publication_date>2026-05-19T17:29:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691995</loc>
  <lastmod>2026-05-19T17:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>永続的隠れ状態と非線形変換によるLSTMの改良（Persistent Hidden States and Nonlinear Transformation for Long Short-Term Memory）</news:title>
   <news:publication_date>2026-05-19T17:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691993</loc>
  <lastmod>2026-05-19T17:29:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのスペクトルバイアス（On the Spectral Bias of Neural Networks）</news:title>
   <news:publication_date>2026-05-19T17:29:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691991</loc>
  <lastmod>2026-05-19T16:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様で解釈可能な分類ルールの学習（Learning Qualitatively Diverse and Interpretable Rules for Classification）</news:title>
   <news:publication_date>2026-05-19T16:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691989</loc>
  <lastmod>2026-05-19T16:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽を“間隔”で予測するモデル：学習されたインターバル表現に基づく予測モデル（A predictive model for music based on learned interval representations）</news:title>
   <news:publication_date>2026-05-19T16:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691987</loc>
  <lastmod>2026-05-19T16:37:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見出しニュースで株価のトレンドを予測する（Using NLP on news headlines to predict index trends）</news:title>
   <news:publication_date>2026-05-19T16:37:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691985</loc>
  <lastmod>2026-05-19T16:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトな深層ニューラルネットワークによる筋電信号からのジェスチャ分類の効率化（Compact Deep Neural Networks for Computationally Efficient Gesture Classification From Electromyography Signals）</news:title>
   <news:publication_date>2026-05-19T16:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691983</loc>
  <lastmod>2026-05-19T16:36:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動する機能的プロソディの文脈依存的変化を写像する変分プロソディモデル（A Variational Prosody Model for Mapping the Context-Sensitive Variation of Functional Prosodic Prototypes）</news:title>
   <news:publication_date>2026-05-19T16:36:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691981</loc>
  <lastmod>2026-05-19T16:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメインをまたぐ変分学習とトリプレット情報（Variational learning across domains with triplet information）</news:title>
   <news:publication_date>2026-05-19T16:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691979</loc>
  <lastmod>2026-05-19T16:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全な深層学習への一歩（Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions）</news:title>
   <news:publication_date>2026-05-19T16:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691977</loc>
  <lastmod>2026-05-19T15:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家族写真から子どもの顔を生成する技術の要点（KINSHIPGAN: SYNTHESIZING OF KINSHIP FACES FROM FAMILY PHOTOS BY REGULARIZING A DEEP FACE NETWORK）</news:title>
   <news:publication_date>2026-05-19T15:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691975</loc>
  <lastmod>2026-05-19T15:44:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tensor Monte Carlo：GPU時代の粒子法の再定義（Tensor Monte Carlo: Particle Methods for the GPU Era）</news:title>
   <news:publication_date>2026-05-19T15:44:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691973</loc>
  <lastmod>2026-05-19T15:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Multi-task WaveNetによる音声合成の簡潔化と高品質化（Multi-task WaveNet: A Multi-task Generative Model for Statistical Parametric Speech Synthesis without Fundamental Frequency Conditions）</news:title>
   <news:publication_date>2026-05-19T15:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691971</loc>
  <lastmod>2026-05-19T15:44:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一インクリメンタルタスクにおける継続学習（Continuous Learning in Single-Incremental-Task Scenarios）</news:title>
   <news:publication_date>2026-05-19T15:44:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691969</loc>
  <lastmod>2026-05-19T15:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FLARECAST：衛星データを用いた宇宙天気のI4.0技術（FLARECAST: an I4.0 technology for space weather using satellite data）</news:title>
   <news:publication_date>2026-05-19T15:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691967</loc>
  <lastmod>2026-05-19T15:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層スペクトル畳み込みネットワークによるハイパースペクトル混合解除（Deep Spectral Convolution Network for Hyperspectral Unmixing）</news:title>
   <news:publication_date>2026-05-19T15:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691965</loc>
  <lastmod>2026-05-19T15:43:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>20質問で学ぶ知識獲得法（Learning-to-Ask: Knowledge Acquisition via 20 Questions）</news:title>
   <news:publication_date>2026-05-19T15:43:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691963</loc>
  <lastmod>2026-05-19T14:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸なマルチ種ホップフィールドモデル（Non-convex Multi-Species Hopfield Models）</news:title>
   <news:publication_date>2026-05-19T14:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691961</loc>
  <lastmod>2026-05-19T14:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変数イテレーティブ・ラーニング制御の設計手順（Multivariable Iterative Learning Control Design Procedures）</news:title>
   <news:publication_date>2026-05-19T14:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691959</loc>
  <lastmod>2026-05-19T14:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速ドローンレースに学ぶ機敏な自律飛行（Deep Drone Racing: Learning Agile Flight in Dynamic Environments）</news:title>
   <news:publication_date>2026-05-19T14:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691957</loc>
  <lastmod>2026-05-19T14:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バーチャルコーデック監督再サンプリングネットワークによる画像圧縮（Virtual Codec Supervised Re-Sampling Network for Image Compression）</news:title>
   <news:publication_date>2026-05-19T14:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691955</loc>
  <lastmod>2026-05-19T14:51:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CTR予測における深層ニューラルネットワークの可視化と理解（Visualizing and Understanding Deep Neural Networks in CTR Prediction）</news:title>
   <news:publication_date>2026-05-19T14:51:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691953</loc>
  <lastmod>2026-05-19T14:51:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的グルーピングによる効率的なセマンティックセグメンテーション（Efficient Semantic Segmentation using Gradual Grouping）</news:title>
   <news:publication_date>2026-05-19T14:51:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691951</loc>
  <lastmod>2026-05-19T14:50:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間系列データにおける注目点の見極め（Focusing on What is Relevant: Time-Series Learning and Understanding using Attention）</news:title>
   <news:publication_date>2026-05-19T14:50:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691949</loc>
  <lastmod>2026-05-19T13:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚・慣性融合による物体検出とマッピング（Visual-Inertial Object Detection and Mapping）</news:title>
   <news:publication_date>2026-05-19T13:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691947</loc>
  <lastmod>2026-05-19T13:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバル意味的一貫性によるゼロショット学習の実装と意義（Global Semantic Consistency for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-05-19T13:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691945</loc>
  <lastmod>2026-05-19T13:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスクからの3D人体形状再構築（Shape-from-Mask: A Deep Learning Based Human Body Shape Reconstruction from Binary Mask Images）</news:title>
   <news:publication_date>2026-05-19T13:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691943</loc>
  <lastmod>2026-05-19T13:58:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネット由来ガウス過程回帰による関数近似と偏微分方程式の解法（Neural-net-induced Gaussian process regression for function approximation and PDE solution）</news:title>
   <news:publication_date>2026-05-19T13:58:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691941</loc>
  <lastmod>2026-05-19T13:58:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と対話しながら学ぶサブゴール監督による効率的な逆強化学習（Human-Interactive Subgoal Supervision for Efficient Inverse Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T13:58:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691939</loc>
  <lastmod>2026-05-19T13:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間構造と空間詳細を同時学習する動画インペインティング（Video Inpainting by Jointly Learning Temporal Structure and Spatial Details）</news:title>
   <news:publication_date>2026-05-19T13:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691937</loc>
  <lastmod>2026-05-19T13:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるDB型白色矮星のスペクトル特徴抽出（Spectral Feature Extraction for DB White Dwarfs through Machine Learning）</news:title>
   <news:publication_date>2026-05-19T13:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691935</loc>
  <lastmod>2026-05-19T13:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度かつ姿勢不変な高忠実度顔正面化モデル（Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization）</news:title>
   <news:publication_date>2026-05-19T13:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691933</loc>
  <lastmod>2026-05-19T13:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ECOCとデータ複雑度で切り拓く多クラス・マイクロアレイ分類（A New ECOC Algorithm for Multiclass Microarray Data Classification）</news:title>
   <news:publication_date>2026-05-19T13:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691931</loc>
  <lastmod>2026-05-19T13:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOOCディスカッションフォーラムの個人化スレッド推薦（Personalized Thread Recommendation for MOOC Discussion Forums）</news:title>
   <news:publication_date>2026-05-19T13:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691929</loc>
  <lastmod>2026-05-19T13:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固定サイズニューラルネットワークの表現力と位相特性（Topological properties of the set of functions generated by neural networks of fixed size）</news:title>
   <news:publication_date>2026-05-19T13:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691927</loc>
  <lastmod>2026-05-19T13:05:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TriResNetによる病理組織画像のタイル単位判定の高精度化（TriResNet: A Deep Triple-stream Residual Network for Histopathology Grading）</news:title>
   <news:publication_date>2026-05-19T13:05:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691925</loc>
  <lastmod>2026-05-19T13:05:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的文生成のための確率的ワッサースタインオートエンコーダ (Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation)</news:title>
   <news:publication_date>2026-05-19T13:05:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691923</loc>
  <lastmod>2026-05-19T13:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疾患関連SNPの同定のためのモデルベースクラスタリング（Model-based clustering for identifying disease-associated SNPs in case-control genome-wide association studies）</news:title>
   <news:publication_date>2026-05-19T13:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691921</loc>
  <lastmod>2026-05-19T12:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コレスポンデンス分析の一般化と機械学習応用（Generalizing Correspondence Analysis for Applications in Machine Learning）</news:title>
   <news:publication_date>2026-05-19T12:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691919</loc>
  <lastmod>2026-05-19T12:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変セグメンテーションにおける星形（Star）形状事前情報の導入（Star Shape Prior in Fully Convolutional Networks for Skin Lesion Segmentation）</news:title>
   <news:publication_date>2026-05-19T12:13:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691917</loc>
  <lastmod>2026-05-19T12:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ia型超新星2017ejbの前駆体に対するX線上限（X-ray Limits on the Progenitor System of the Type Ia Supernova 2017ejb）</news:title>
   <news:publication_date>2026-05-19T12:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691915</loc>
  <lastmod>2026-05-19T12:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画像に対応した音声映像シーン応答のエンドツーエンドモデル（End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features）</news:title>
   <news:publication_date>2026-05-19T12:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691913</loc>
  <lastmod>2026-05-19T12:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトな離散符号による埋め込み表現の学習（Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations）</news:title>
   <news:publication_date>2026-05-19T12:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691911</loc>
  <lastmod>2026-05-19T12:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短時間客観的可解度と短時間スペクトル振幅二乗平均誤差の関係（On the Relationship Between Short-Time Objective Intelligibility and Short-Time Spectral-Amplitude Mean-Square Error for Speech Enhancement）</news:title>
   <news:publication_date>2026-05-19T12:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691909</loc>
  <lastmod>2026-05-19T12:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサー数・配置・システム次元性が流体のスパース再構成に与える影響（Interplay of Sensor Quantity, Placement and System Dimensionality on Energy Sparse Reconstruction of Fluid Flows）</news:title>
   <news:publication_date>2026-05-19T12:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691907</loc>
  <lastmod>2026-05-19T11:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークの量子化による効率的推論（Quantizing deep convolutional networks for efficient inference: A whitepaper）</news:title>
   <news:publication_date>2026-05-19T11:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691905</loc>
  <lastmod>2026-05-19T11:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストな判別分析の理論と実践（Target Robust Discriminant Analysis）</news:title>
   <news:publication_date>2026-05-19T11:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691903</loc>
  <lastmod>2026-05-19T11:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光パルス位置変調（PPM）リンクの距離依存性と背景雑音下での情報効率（Range Dependence of an Optical Pulse Position Modulation Link in the Presence of Background Noise）</news:title>
   <news:publication_date>2026-05-19T11:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691901</loc>
  <lastmod>2026-05-19T11:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コマ・ベレニケス矮小銀河における初期質量関数の深層近赤外観測による解析（THE INITIAL MASS FUNCTION IN THE COMA BERENICES DWARF GALAXY FROM DEEP NEAR-INFRARED HST OBSERVATIONS）</news:title>
   <news:publication_date>2026-05-19T11:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691899</loc>
  <lastmod>2026-05-19T11:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震波データから深層学習で地下水貯留量を推定する（Estimation of groundwater storage from seismic data using deep learning）</news:title>
   <news:publication_date>2026-05-19T11:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691897</loc>
  <lastmod>2026-05-19T11:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模画像データ群における解釈可能な発見検出（Interpretable Discovery in Large Image Data Sets）</news:title>
   <news:publication_date>2026-05-19T11:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691895</loc>
  <lastmod>2026-05-19T11:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用により学習するインスタンスセグメンテーション（Learning Instance Segmentation by Interaction）</news:title>
   <news:publication_date>2026-05-19T11:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691893</loc>
  <lastmod>2026-05-19T10:18:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア小型化と画像再構成のトレードオフを覆す試み（Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?）</news:title>
   <news:publication_date>2026-05-19T10:18:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691891</loc>
  <lastmod>2026-05-19T10:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子キッチンシンク：近接期量子コンピュータ向け機械学習アルゴリズム（Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers）</news:title>
   <news:publication_date>2026-05-19T10:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691889</loc>
  <lastmod>2026-05-19T10:08:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Countdown Regressionによる生存予測の鋭さと較正性の向上（Countdown Regression: Sharp and Calibrated Survival Predictions）</news:title>
   <news:publication_date>2026-05-19T10:08:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691887</loc>
  <lastmod>2026-05-19T10:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Par4Sim – 適応型パラフレーズによる文章簡易化（Par4Sim – Adaptive Paraphrasing for Text Simplification）</news:title>
   <news:publication_date>2026-05-19T10:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691885</loc>
  <lastmod>2026-05-19T10:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン鞍点問題とナップザック付きオンライン凸最適化の解法（The Online Saddle Point Problem and Online Convex Optimization with Knapsacks）</news:title>
   <news:publication_date>2026-05-19T10:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691883</loc>
  <lastmod>2026-05-19T10:06:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>図に対するグラフ重み付きモデルの学習（Learning Graph Weighted Models on Pictures）</news:title>
   <news:publication_date>2026-05-19T10:06:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691881</loc>
  <lastmod>2026-05-19T10:06:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fashion-Gen: Generative Fashion Datasetとチャレンジ（Fashion-Gen: The Generative Fashion Dataset and Challenge）</news:title>
   <news:publication_date>2026-05-19T10:06:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691879</loc>
  <lastmod>2026-05-19T09:15:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>良い局所最小値はスパース復元で幅があるのか（Are good local minima wide in sparse recovery?）</news:title>
   <news:publication_date>2026-05-19T09:15:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691877</loc>
  <lastmod>2026-05-19T09:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T09:13:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T08:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の活動のためのマルチモーダル表現学習（Learning Multimodal Representations for Unseen Activities）</news:title>
   <news:publication_date>2026-05-19T08:14:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-19T08:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691859</loc>
  <lastmod>2026-05-19T08:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移調不変な音程特徴量の学習（Learning transposition-invariant interval features from symbolic music and audio）</news:title>
   <news:publication_date>2026-05-19T08:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691857</loc>
  <lastmod>2026-05-19T08:13:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T08:13:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691855</loc>
  <lastmod>2026-05-19T08:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T08:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691853</loc>
  <lastmod>2026-05-19T08:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T08:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691851</loc>
  <lastmod>2026-05-19T07:21:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス意識型のニューラルアーキテクチャ探索が変える現場（DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures）</news:title>
   <news:publication_date>2026-05-19T07:21:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-19T07:11:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T07:11:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691845</loc>
  <lastmod>2026-05-19T07:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ単位の分類のための凸解法（A convex method for classification of groups of examples）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691843</loc>
  <lastmod>2026-05-19T07:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血流中の赤血球形状を自動分類する手法（Classification of red blood cell shapes in flow using outlier tolerant machine learning）</news:title>
   <news:publication_date>2026-05-19T07:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691841</loc>
  <lastmod>2026-05-19T07:10:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイジー値・比較モデルにおけるインスタンス最適性（Instance-Optimality in the Noisy Value-and Comparison-Model）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691839</loc>
  <lastmod>2026-05-19T07:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691837</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T06:18:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691835</loc>
  <lastmod>2026-05-19T06:18:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CaloriNet: プライベート環境でのシルエットを用いた消費カロリー推定（CaloriNet: From silhouettes to calorie estimation in private environments）</news:title>
   <news:publication_date>2026-05-19T06:18:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691833</loc>
  <lastmod>2026-05-19T06:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル不確実性に強いブースティング手法（Robust and Efficient Boosting Method using the Conditional Risk）</news:title>
   <news:publication_date>2026-05-19T06:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691831</loc>
  <lastmod>2026-05-19T06:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スライス・ワッサースタインフロー（Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions）</news:title>
   <news:publication_date>2026-05-19T06:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691829</loc>
  <lastmod>2026-05-19T06:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム多孔質媒質を通るストークス流のデータ駆動型次元削減（A data-driven model order reduction approach for Stokes flow through random porous media）</news:title>
   <news:publication_date>2026-05-19T06:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691827</loc>
  <lastmod>2026-05-19T06:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T06:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691825</loc>
  <lastmod>2026-05-19T06:17:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習による資源スケジューリング新手法（A New Approach for Resource Scheduling with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T06:17:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691823</loc>
  <lastmod>2026-05-19T05:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の動作生成におけるRNNと敵対的学習の統合（Combining Recurrent Neural Networks and Adversarial Training for Human Motion Modelling, Synthesis and Control）</news:title>
   <news:publication_date>2026-05-19T05:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691821</loc>
  <lastmod>2026-05-19T05:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業制御システムにおけるサイバー攻撃検知と畳み込みニューラルネットワーク（Detecting Cyberattacks in Industrial Control Systems Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-19T05:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691819</loc>
  <lastmod>2026-05-19T05:26:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ensemble p-Laplacian正則化によるリモートセンシング画像認識（Ensemble p-Laplacian Regularization for Remote Sensing Image Recognition）</news:title>
   <news:publication_date>2026-05-19T05:26:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691817</loc>
  <lastmod>2026-05-19T05:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外科手技の動作分割と認識に深層強化学習を適用する（Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification）</news:title>
   <news:publication_date>2026-05-19T05:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691815</loc>
  <lastmod>2026-05-19T05:25:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型アプリケーション保守が変える現場運用（Data-Driven Application Maintenance: Views from the Trenches）</news:title>
   <news:publication_date>2026-05-19T05:25:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691813</loc>
  <lastmod>2026-05-19T05:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラマルキアン進化による畳み込みニューラルネットワークの最適化（Lamarckian Evolution of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-19T05:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691811</loc>
  <lastmod>2026-05-19T05:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフ p-ラプラシアン正則化によるリモートセンシング画像認識（Hypergraph p-Laplacian Regularization for Remote Sensing Image Recognition）</news:title>
   <news:publication_date>2026-05-19T05:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691809</loc>
  <lastmod>2026-05-19T04:34:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行為―認知ループにおける能動推論の拡張（Expanding the Active Inference Landscape: More Intrinsic Motivations in the Perception-Action Loop）</news:title>
   <news:publication_date>2026-05-19T04:34:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691807</loc>
  <lastmod>2026-05-19T04:34:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然な力学の頑健性を量る—基底境界を越えて（Beyond Basins of Attraction: Quantifying Robustness of Natural Dynamics）</news:title>
   <news:publication_date>2026-05-19T04:34:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/691805</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GrCAN：Gradient Boost Convolutional Autoencoder with Neural Decision Forest（GrCAN: Gradient Boost Convolutional Autoencoder with Neural Decision Forest）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691803</loc>
  <lastmod>2026-05-19T04:33:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ガウス過程を用いたベイズ推論による汚染源局在化（Deep Gaussian Process-Based Bayesian Inference for Contaminant Source Localization）</news:title>
   <news:publication_date>2026-05-19T04:33:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691801</loc>
  <lastmod>2026-05-19T04:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステガノ解析の視点から見た敵対的例の検出（Detection based Defense against Adversarial Examples from the Steganalysis Point of View）</news:title>
   <news:publication_date>2026-05-19T04:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691799</loc>
  <lastmod>2026-05-19T04:32:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書誘導型編集ネットワークによるパラフレーズ生成（Dictionary-Guided Editing Networks for Paraphrase Generation）</news:title>
   <news:publication_date>2026-05-19T04:32:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691797</loc>
  <lastmod>2026-05-19T04:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットを用いた認知モデル学習（Learning Cognitive Models using Neural Networks）</news:title>
   <news:publication_date>2026-05-19T04:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691795</loc>
  <lastmod>2026-05-19T03:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟な物理予測のためのニューラル表現（Flexible Neural Representation for Physics Prediction）</news:title>
   <news:publication_date>2026-05-19T03:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691793</loc>
  <lastmod>2026-05-19T03:41:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈手法の頑健性について（On the Robustness of Interpretability Methods）</news:title>
   <news:publication_date>2026-05-19T03:41:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691791</loc>
  <lastmod>2026-05-19T03:41:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差補償付き量子化SGDと大規模分散最適化への応用（Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization）</news:title>
   <news:publication_date>2026-05-19T03:41:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691789</loc>
  <lastmod>2026-05-19T03:41:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのある手書きバングラ文字の画素レベル再構成と分類（Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters）</news:title>
   <news:publication_date>2026-05-19T03:41:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691787</loc>
  <lastmod>2026-05-19T03:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話のためのコヒーレンスモデル（Coherence Models for Dialogue）</news:title>
   <news:publication_date>2026-05-19T03:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691785</loc>
  <lastmod>2026-05-19T03:40:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配敵対的訓練がもたらす変化（Gradient Adversarial Training of Neural Networks）</news:title>
   <news:publication_date>2026-05-19T03:40:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691783</loc>
  <lastmod>2026-05-19T03:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>21世紀の理科教育（Science Education in the 21st Century）</news:title>
   <news:publication_date>2026-05-19T03:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691781</loc>
  <lastmod>2026-05-19T02:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予約ありキューの均衡と学習（Equilibrium and Learning in Queues with Advance Reservations）</news:title>
   <news:publication_date>2026-05-19T02:49:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691779</loc>
  <lastmod>2026-05-19T02:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベースの埋め込みモデルを解釈する教育的アプローチ（Interpreting Embedding Models of Knowledge Bases: A Pedagogical Approach）</news:title>
   <news:publication_date>2026-05-19T02:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691777</loc>
  <lastmod>2026-05-19T02:38:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散乱復元に強い学習モデルの安定性（Stability of Scattering Decoder for Nonlinear Diffractive Imaging）</news:title>
   <news:publication_date>2026-05-19T02:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691775</loc>
  <lastmod>2026-05-19T02:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地平線を使った単眼障害物検出の新視点（Learning What’s Above and What’s Below: Horizon Approach to Monocular Obstacle Detection）</news:title>
   <news:publication_date>2026-05-19T02:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691773</loc>
  <lastmod>2026-05-19T02:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人口統計情報なしでの繰返し損失最小化における公平性（Fairness Without Demographics in Repeated Loss Minimization）</news:title>
   <news:publication_date>2026-05-19T02:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691771</loc>
  <lastmod>2026-05-19T02:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>南極深層氷コアに記録された気候エントロピー生成（Climate entropy production recorded in a deep Antarctic ice core）</news:title>
   <news:publication_date>2026-05-19T02:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691769</loc>
  <lastmod>2026-05-19T02:37:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的関係表現をニューラルネットに注入する手法（Injecting Relational Structural Representation in Neural Networks for Question Similarity）</news:title>
   <news:publication_date>2026-05-19T02:37:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691767</loc>
  <lastmod>2026-05-19T01:46:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁性二次元材料のデータ駆動研究（Data-driven studies of magnetic two-dimensional materials）</news:title>
   <news:publication_date>2026-05-19T01:46:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691765</loc>
  <lastmod>2026-05-19T01:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エピソード記憶の意味的圧縮（Semantic Compression of Episodic Memories）</news:title>
   <news:publication_date>2026-05-19T01:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691763</loc>
  <lastmod>2026-05-19T01:46:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信号灯と道路標識の同時検出を可能にする階層的深層構造とミニバッチ選択法（A Hierarchical Deep Architecture and Mini-Batch Selection Method For Joint Traffic Sign and Light Detection）</news:title>
   <news:publication_date>2026-05-19T01:46:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691761</loc>
  <lastmod>2026-05-19T01:46:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コーパス複製タスクが示す意味抽出の本質（The Corpus Replication Task）</news:title>
   <news:publication_date>2026-05-19T01:46:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691759</loc>
  <lastmod>2026-05-19T01:45:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続値強化学習における過学習と汎化の解剖（A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T01:45:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691757</loc>
  <lastmod>2026-05-19T01:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディア上の論争を立場要約で説明する（Explaining Controversy on Social Media via Stance Summarization）</news:title>
   <news:publication_date>2026-05-19T01:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691755</loc>
  <lastmod>2026-05-19T01:45:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>課題指向の畳み込み再帰モデルによる視覚システムの理解（Task-Driven Convolutional Recurrent Models of the Visual System）</news:title>
   <news:publication_date>2026-05-19T01:45:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691753</loc>
  <lastmod>2026-05-19T00:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の仕組みと実務への示唆（How Deep Learning Works）</news:title>
   <news:publication_date>2026-05-19T00:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691751</loc>
  <lastmod>2026-05-19T00:53:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッブル・フロンティア・フィールドにおける遠方銀河の拡大バイアス：波動（ウェーブ）対粒子ダークマターの検証（MAGNIFICATION BIAS OF DISTANT GALAXIES IN THE HUBBLE FRONTIER FIELDS: TESTING WAVE VS. PARTICLE DARK MATTER PREDICTIONS）</news:title>
   <news:publication_date>2026-05-19T00:53:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691749</loc>
  <lastmod>2026-05-19T00:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホットジュピター大気における乱流駆動熱・運動エネルギーフラックス（Turbulence-driven thermal and kinetic energy fluxes in the atmospheres of hot Jupiters）</news:title>
   <news:publication_date>2026-05-19T00:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691747</loc>
  <lastmod>2026-05-19T00:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hybrid Bayesian Eigenobjects（Hybrid Bayesian Eigenobjects: Combining Linear Subspace and Deep Network Methods for 3D Robot Vision）</news:title>
   <news:publication_date>2026-05-19T00:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691745</loc>
  <lastmod>2026-05-19T00:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ガウス型グラフィカルモデルにおける逐次変化点検出（Sequential change-point detection in high-dimensional Gaussian graphical models）</news:title>
   <news:publication_date>2026-05-19T00:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691743</loc>
  <lastmod>2026-05-19T00:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RUDDERによる遅延報酬への帰属問題の解決（RUDDER: Return Decomposition for Delayed Rewards）</news:title>
   <news:publication_date>2026-05-19T00:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691741</loc>
  <lastmod>2026-05-19T00:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交互最小化によるReLUネットワーク学習（Learning ReLU Networks via Alternating Minimization）</news:title>
   <news:publication_date>2026-05-19T00:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691739</loc>
  <lastmod>2026-05-19T00:00:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸関数と対数対数凸関数を近似するニューラルネットワークとポシノミアルモデル（Log-sum-exp neural networks and posynomial models for convex and log-log-convex data）</news:title>
   <news:publication_date>2026-05-19T00:00:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691737</loc>
  <lastmod>2026-05-19T00:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから現実へ――布など変形物体操作の強化学習による移転学習（Sim-to-Real Reinforcement Learning for Deformable Object Manipulation）</news:title>
   <news:publication_date>2026-05-19T00:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691735</loc>
  <lastmod>2026-05-19T00:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓不整脈分類におけるSVMと象群最適化の組合せ（Combining Support Vector Machine and Elephant Herding Optimization for Cardiac Arrhythmias）</news:title>
   <news:publication_date>2026-05-19T00:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>エッジデバイス向け機械学習の開発と展開の再考 (Rethinking Machine Learning Development and Deployment for Edge Devices)</news:title>
   <news:publication_date>2026-05-18T23:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691731</loc>
  <lastmod>2026-05-18T23:58:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>博物館におけるゲーミフィケーションとデジタルネイティブへの応用（Gamification for Digitally Native Learners in Museums）</news:title>
   <news:publication_date>2026-05-18T23:58:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691729</loc>
  <lastmod>2026-05-18T23:58:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均質対象の散乱係数と波イメージングにおけ別と識別への応用（Scattering Coefficients of Inhomogeneous Objects and Their Application in Target Classification in Wave Imaging）</news:title>
   <news:publication_date>2026-05-18T23:58:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691727</loc>
  <lastmod>2026-05-18T23:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジインテリジェンス：デバイスとエッジの協調によるオンデマンドDNN共推論（Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy）</news:title>
   <news:publication_date>2026-05-18T23:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691725</loc>
  <lastmod>2026-05-18T23:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語デカスロン：マルチタスク学習を質問応答として統一する（The Natural Language Decathlon: Multitask Learning as Question Answering）</news:title>
   <news:publication_date>2026-05-18T23:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691723</loc>
  <lastmod>2026-05-18T23:06:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InfoCatVAEによるカテゴリ型変分オートエンコーダを用いた表現学習（InfoCatVAE: Representation Learning with Categorical Variational Autoencoders）</news:title>
   <news:publication_date>2026-05-18T23:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691721</loc>
  <lastmod>2026-05-18T23:06:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズだらけでも十分か ― 医療器具の姿勢推定における注釈ノイズの影響（How Bad is Good enough: Noisy annotations for instrument pose estimation）</news:title>
   <news:publication_date>2026-05-18T23:06:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691719</loc>
  <lastmod>2026-05-18T23:05:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重ラジオレリック銀河団Abell 3376のX線解析と衝撃波の解明（X-ray study of the double radio relic Abell 3376 with Suzaku）</news:title>
   <news:publication_date>2026-05-18T23:05:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691717</loc>
  <lastmod>2026-05-18T23:04:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定論的微分可能模倣学習によるニューラルパーサ学習（Learning Neural Parsers with Deterministic Differentiable Imitation Learning）</news:title>
   <news:publication_date>2026-05-18T23:04:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691715</loc>
  <lastmod>2026-05-18T23:04:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き画像生成による物体ランドマークの教師なし学習 (Unsupervised Learning of Object Landmarks through Conditional Image Generation)</news:title>
   <news:publication_date>2026-05-18T23:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691713</loc>
  <lastmod>2026-05-18T23:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化潜在変数を用いた半教師付き意味解析（STRUCTVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing）</news:title>
   <news:publication_date>2026-05-18T23:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691711</loc>
  <lastmod>2026-05-18T22:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対応関係の重み付けを用いたメトリック駆動の2-D/3-Dレジストレーション学習 (Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Registration)</news:title>
   <news:publication_date>2026-05-18T22:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691709</loc>
  <lastmod>2026-05-18T22:12:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的入れ子分散削減法による非凸最適化の加速（Stochastic Nested Variance Reduction for Nonconvex Optimization）</news:title>
   <news:publication_date>2026-05-18T22:12:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691707</loc>
  <lastmod>2026-05-18T22:11:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタゲノムデータからウイルスを見つける深層学習（Identifying viruses from metagenomic data by deep learning）</news:title>
   <news:publication_date>2026-05-18T22:11:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691705</loc>
  <lastmod>2026-05-18T22:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトニック・ハイパークリスタルの非線形光学：光リミッティングとハイパーコンピューティング（Nonlinear optics of photonic hyper-crystals: optical limiting and hyper-computing）</news:title>
   <news:publication_date>2026-05-18T22:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691703</loc>
  <lastmod>2026-05-18T22:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1層ReLUネットワークの学習と勾配降下法による収束保証（Learning One-hidden-layer ReLU Networks via Gradient Descent）</news:title>
   <news:publication_date>2026-05-18T22:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691701</loc>
  <lastmod>2026-05-18T22:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム特徴量Stein不一致度（Random Feature Stein Discrepancies）</news:title>
   <news:publication_date>2026-05-18T22:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691699</loc>
  <lastmod>2026-05-18T22:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四元数畳み込みニューラルネットワークによるエンドツーエンド自動音声認識（Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-05-18T22:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691697</loc>
  <lastmod>2026-05-18T21:18:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映画レビューの意見動態を捉える潜在状態モデル（Opinion Dynamics Modeling for Movie Review Transcripts Classification with Hidden Conditional Random Fields）</news:title>
   <news:publication_date>2026-05-18T21:18:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691695</loc>
  <lastmod>2026-05-18T21:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療用MR画像の画像間変換におけるGAN比較（GENERATIVE ADVERSARIAL NETWORKS FOR IMAGE-TO-IMAGE TRANSLATION ON MULTI-CONTRAST MR IMAGES - A COMPARISON OF CYCLEGAN AND UNIT）</news:title>
   <news:publication_date>2026-05-18T21:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691693</loc>
  <lastmod>2026-05-18T21:17:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵文字の共起ネットワークを用いた埋め込み学習（Learning Emoji Embeddings using Emoji Co-occurrence Network Graph）</news:title>
   <news:publication_date>2026-05-18T21:17:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691691</loc>
  <lastmod>2026-05-18T21:16:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数サンプルから最良を選ぶ系列サンプリング（Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective）</news:title>
   <news:publication_date>2026-05-18T21:16:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691689</loc>
  <lastmod>2026-05-18T21:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EDGES High-Bandによる初期銀河パラメータの制約（Constraints on Parameters of Early Galaxies from EDGES High-Band）</news:title>
   <news:publication_date>2026-05-18T21:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691687</loc>
  <lastmod>2026-05-18T21:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フーリエ変換サロゲートによるクラス不均衡への対処（Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates）</news:title>
   <news:publication_date>2026-05-18T21:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691685</loc>
  <lastmod>2026-05-18T21:16:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>802.11acエッジネットワークでの低遅延・高スループット実現（Quick &amp;amp; Plenty: Achieving Low Delay &amp;amp; High Rate in 802.11ac Edge Networks）</news:title>
   <news:publication_date>2026-05-18T21:16:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691683</loc>
  <lastmod>2026-05-18T20:24:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロン活性時系列からのネットワーク推定手法のレビュー (A Review of Network Inference Techniques for Neural Activation Time Series)</news:title>
   <news:publication_date>2026-05-18T20:24:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691681</loc>
  <lastmod>2026-05-18T20:23:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習システムの組合せテスト（Combinatorial Testing for Deep Learning Systems）</news:title>
   <news:publication_date>2026-05-18T20:23:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691679</loc>
  <lastmod>2026-05-18T20:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインニュースのクリックベイト検出にニューラルネットを使う（Using Neural Network for Identifying Clickbaits in Online News Media）</news:title>
   <news:publication_date>2026-05-18T20:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691677</loc>
  <lastmod>2026-05-18T20:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEFRAG: 深層ユークリッド特徴表現の適応による整備（DEFRAG: DEEP EUCLIDEAN FEATURE REPRESENTATIONS THROUGH ADAPTATION ON THE GRASSMANN MANIFOLD）</news:title>
   <news:publication_date>2026-05-18T20:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691675</loc>
  <lastmod>2026-05-18T20:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張ニューラルネットワークを用いた強化学習（Reinforcement Learning using Augmented Neural Networks）</news:title>
   <news:publication_date>2026-05-18T20:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691673</loc>
  <lastmod>2026-05-18T20:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率回帰の非パラメトリック較正（Non-Parametric Calibration of Probabilistic Regression）</news:title>
   <news:publication_date>2026-05-18T20:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691671</loc>
  <lastmod>2026-05-18T20:21:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己重み付けマルチカーネル学習によるグラフベースクラスタリングと半教師あり分類（Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification）</news:title>
   <news:publication_date>2026-05-18T20:21:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691669</loc>
  <lastmod>2026-05-18T19:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー学習における動的投票と放射線オミクス応用（Dynamic voting in multi-view learning for radiomics applications）</news:title>
   <news:publication_date>2026-05-18T19:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691667</loc>
  <lastmod>2026-05-18T19:29:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたファクトチェックの展望（Automated Fact Checking: Task formulations, methods and future directions）</news:title>
   <news:publication_date>2026-05-18T19:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691665</loc>
  <lastmod>2026-05-18T19:28:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカルグループ矮小銀河の初期進化：星形成と超新星フィードバック（On the early evolution of Local Group dwarf galaxy types: star formation and supernova feedback）</news:title>
   <news:publication_date>2026-05-18T19:28:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691663</loc>
  <lastmod>2026-05-18T19:28:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なるパラダイム間での畳み込みネットワーク事前学習が脳内EEGデコーディングを改善する（Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding）</news:title>
   <news:publication_date>2026-05-18T19:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691661</loc>
  <lastmod>2026-05-18T19:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ΛΛ−ΞN混合がもたらす非メゾニック崩壊の変化（Eﬀects of ΛΛ −ΞN mixing in the decay of S = −2 hypernuclei）</news:title>
   <news:publication_date>2026-05-18T19:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691659</loc>
  <lastmod>2026-05-18T19:27:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダークエネルギー方程式の遅延変化の制約（Constraining late-time transitions in the dark energy equation of state）</news:title>
   <news:publication_date>2026-05-18T19:27:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691657</loc>
  <lastmod>2026-05-18T19:27:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀行の実運用に耐える顔照合の越境対応（Cross-Domain Deep Face Matching for Real Banking Security Systems）</news:title>
   <news:publication_date>2026-05-18T19:27:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691655</loc>
  <lastmod>2026-05-18T18:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スキル経験カタログ（Skilled Experience Catalogue: A Skill-Balancing Mechanism for Non-Player Characters using Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-18T18:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691653</loc>
  <lastmod>2026-05-18T18:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次自動運転車両の動的リスク評価を深層学習で実現する（Dynamic Risk Assessment for Vehicles of Higher Automation Levels by Deep Learning）</news:title>
   <news:publication_date>2026-05-18T18:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691651</loc>
  <lastmod>2026-05-18T18:35:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏極深部非弾性散乱における包摂的重フレーバー生成への NLO QCD 補正 (Next-to-Leading Order QCD Corrections to Inclusive Heavy-Flavor Production in Polarized Deep-Inelastic Scattering)</news:title>
   <news:publication_date>2026-05-18T18:35:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691649</loc>
  <lastmod>2026-05-18T18:35:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習と敵対的生成ネットワークによる発作予測（Semi-supervised Seizure Prediction with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-18T18:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691647</loc>
  <lastmod>2026-05-18T18:35:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実時間歩行者追跡のための深い類似度メトリック学習（Deep Similarity Metric Learning for Real-Time Pedestrian Tracking）</news:title>
   <news:publication_date>2026-05-18T18:35:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691645</loc>
  <lastmod>2026-05-18T18:34:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子の形状ゆらぎと深層散乱の関係（Proton shape fluctuations and its relation to DIS）</news:title>
   <news:publication_date>2026-05-18T18:34:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691643</loc>
  <lastmod>2026-05-18T18:34:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーマン最適量子化と航空交通解析への応用（Optimal Riemannian quantization with an application to air traffic analysis）</news:title>
   <news:publication_date>2026-05-18T18:34:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691641</loc>
  <lastmod>2026-05-18T17:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログからのニュースイベント抽出（Extracting News Events from Microblogs）</news:title>
   <news:publication_date>2026-05-18T17:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691639</loc>
  <lastmod>2026-05-18T17:43:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳動脈瘤の壁応力推定におけるZernike畳み込みニューラルネットワーク（Wall Stress Estimation of Cerebral Aneurysm based on Zernike Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-18T17:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691637</loc>
  <lastmod>2026-05-18T17:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルタンジェントカーネルが示す学習の姿（Neural Tangent Kernel: Convergence and Generalization in Neural Networks）</news:title>
   <news:publication_date>2026-05-18T17:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691635</loc>
  <lastmod>2026-05-18T17:42:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的安全ベイズ最適化の実務的解説（Stagewise Safe Bayesian Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-05-18T17:42:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691633</loc>
  <lastmod>2026-05-18T17:42:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる分散二次最適化アルゴリズム（A Distributed Second-Order Algorithm You Can Trust）</news:title>
   <news:publication_date>2026-05-18T17:42:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691631</loc>
  <lastmod>2026-05-18T17:42:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Doubly Nested Networkによるリソース効率化推論（Doubly Nested Network for Resource-Efficient Inference）</news:title>
   <news:publication_date>2026-05-18T17:42:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691629</loc>
  <lastmod>2026-05-18T17:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル付き確率的ブロックモデルにおける効率的推論（Efficient inference in stochastic block models with vertex labels）</news:title>
   <news:publication_date>2026-05-18T17:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691627</loc>
  <lastmod>2026-05-18T16:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>流体流のエンドツーエンドと逐次データ駆動学習の評価 (Assessment of End-to-End and Sequential Data-driven Learning of Fluid Flows)</news:title>
   <news:publication_date>2026-05-18T16:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691625</loc>
  <lastmod>2026-05-18T16:50:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誰にとって解釈可能かを問う役割モデル（Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems）</news:title>
   <news:publication_date>2026-05-18T16:50:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691623</loc>
  <lastmod>2026-05-18T16:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビット当たりネットワークか、ネットワーク当たりビットか（Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit?）</news:title>
   <news:publication_date>2026-05-18T16:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691621</loc>
  <lastmod>2026-05-18T16:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データのための非同期分散期待値最大化アルゴリズム（An Asynchronous Distributed Expectation Maximization Algorithm For Massive Data: The DEM Algorithm）</news:title>
   <news:publication_date>2026-05-18T16:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691619</loc>
  <lastmod>2026-05-18T16:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重散乱媒体のイメージングを終端学習型ニューラルネットで（Multiple Scattering Media Imaging via End-to-End Neural Network）</news:title>
   <news:publication_date>2026-05-18T16:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691617</loc>
  <lastmod>2026-05-18T16:49:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配列だけで化合物－タンパク質親和性を読む（DeepAffinity: Interpretable Deep Learning of Compound–Protein Affinity）</news:title>
   <news:publication_date>2026-05-18T16:49:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691615</loc>
  <lastmod>2026-05-18T16:48:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己説明型ニューラルネットワークによる頑健な解釈性の追求 (Towards Robust Interpretability with Self-Explaining Neural Networks)</news:title>
   <news:publication_date>2026-05-18T16:48:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691613</loc>
  <lastmod>2026-05-18T15:56:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像全体の注釈を人機協調で効率化するインターフェース（Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation）</news:title>
   <news:publication_date>2026-05-18T15:56:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691611</loc>
  <lastmod>2026-05-18T15:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多課題転移学習における不確実性（Uncertainty in Multitask Transfer Learning）</news:title>
   <news:publication_date>2026-05-18T15:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691609</loc>
  <lastmod>2026-05-18T15:56:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械読解の統合フレームワーク（Jack the Reader – A Machine Reading Framework）</news:title>
   <news:publication_date>2026-05-18T15:56:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691607</loc>
  <lastmod>2026-05-18T15:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定性的および定量的因子を扱うガウス過程モデリングへの潜在変数アプローチ (A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors)</news:title>
   <news:publication_date>2026-05-18T15:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691605</loc>
  <lastmod>2026-05-18T15:55:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習と浅層学習の簡易融合による音響シーン分類（A SIMPLE FUSION OF DEEP AND SHALLOW LEARNING FOR ACOUSTIC SCENE CLASSIFICATION）</news:title>
   <news:publication_date>2026-05-18T15:55:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691603</loc>
  <lastmod>2026-05-18T15:54:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>植え込み型スパース構造問題の還元と計算下界（Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure）</news:title>
   <news:publication_date>2026-05-18T15:54:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691601</loc>
  <lastmod>2026-05-18T15:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的サロゲートモデルにおける「局所性」の定義（Defining Locality for Surrogates in Post-hoc Interpretability）</news:title>
   <news:publication_date>2026-05-18T15:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691599</loc>
  <lastmod>2026-05-18T15:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所深層特徴学習による堅牢な顔スプーフィング検出（On the Learning of Deep Local Features for Robust Face Spoofing Detection）</news:title>
   <news:publication_date>2026-05-18T15:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691597</loc>
  <lastmod>2026-05-18T15:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Global-Connected Net と Generalized Multi-Piecewise ReLU の要点解説（Deep Global-Connected Net With The Generalized Multi-Piecewise ReLU Activation in Deep Learning）</news:title>
   <news:publication_date>2026-05-18T15:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691595</loc>
  <lastmod>2026-05-18T15:02:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D超音波から標準断面を自動検出する反復変換ネットワーク（Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network）</news:title>
   <news:publication_date>2026-05-18T15:02:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691593</loc>
  <lastmod>2026-05-18T15:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HairNetによる単一視点からの3Dヘア再構築（HairNet: Single-View Hair Reconstruction using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-18T15:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691591</loc>
  <lastmod>2026-05-18T15:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薄い弾性シート上の水面に浮かぶハイドロエラスティック波紋（Hydroelastic wake on a thin elastic sheet floating on water）</news:title>
   <news:publication_date>2026-05-18T15:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691589</loc>
  <lastmod>2026-05-18T15:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしグラフ埋め込みの意味内容の探索（Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study）</news:title>
   <news:publication_date>2026-05-18T15:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691587</loc>
  <lastmod>2026-05-18T15:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子スケール画像から相図を再構築する方法（Learning from imperfections: constructing phase diagrams from atomic imaging of fluctuations）</news:title>
   <news:publication_date>2026-05-18T15:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691585</loc>
  <lastmod>2026-05-18T14:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定量MRI：深層学習でT1・T2・プロトン密度を絶対値で推定する手法（Quantitative MRI – Absolute T1, T2 and Proton Density Parameters from Deep Learning）</news:title>
   <news:publication_date>2026-05-18T14:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691583</loc>
  <lastmod>2026-05-18T14:09:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CSIベースの屋外位置推定が変える現場応用（CSI-based Outdoor Localization for Massive MIMO: Experiments with a Learning Approach）</news:title>
   <news:publication_date>2026-05-18T14:09:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691581</loc>
  <lastmod>2026-05-18T14:09:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乱流補正におけるニューラルネットワークのフィードバック手法（Turbulence correction with artificial neural networks）</news:title>
   <news:publication_date>2026-05-18T14:09:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691579</loc>
  <lastmod>2026-05-18T14:08:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COHERENTによるニュートリノ一般化相互作用の解析（COHERENT analysis of neutrino generalized interactions）</news:title>
   <news:publication_date>2026-05-18T14:08:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691577</loc>
  <lastmod>2026-05-18T14:08:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HybridNetによる動的システム予測の統合手法（HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems）</news:title>
   <news:publication_date>2026-05-18T14:08:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691575</loc>
  <lastmod>2026-05-18T14:07:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fast CapsNet for Lung Cancer Screening（Fast CapsNet for Lung Cancer Screening）</news:title>
   <news:publication_date>2026-05-18T14:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691573</loc>
  <lastmod>2026-05-18T14:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従業員離職予測 (Employee Attrition Prediction)</news:title>
   <news:publication_date>2026-05-18T14:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691571</loc>
  <lastmod>2026-05-18T13:15:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内在する微小敵対的摂動への脆弱性の注入（Built-in Vulnerabilities to Imperceptible Adversarial Perturbations）</news:title>
   <news:publication_date>2026-05-18T13:15:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691569</loc>
  <lastmod>2026-05-18T13:15:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフィードバックを用いた対比ヘッブ学習（Contrastive Hebbian Learning with Random Feedback Weights）</news:title>
   <news:publication_date>2026-05-18T13:15:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691567</loc>
  <lastmod>2026-05-18T13:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続深さニューラルネットワークの提案（Neural Ordinary Differential Equations）</news:title>
   <news:publication_date>2026-05-18T13:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691565</loc>
  <lastmod>2026-05-18T13:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コード意味理解のためのニューラル表現（Neural Code Comprehension）</news:title>
   <news:publication_date>2026-05-18T13:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691563</loc>
  <lastmod>2026-05-18T13:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>総変動法による重力波データのノイズ除去評価（Total-variation methods for gravitational-wave denoising: performance tests on Advanced LIGO data）</news:title>
   <news:publication_date>2026-05-18T13:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691561</loc>
  <lastmod>2026-05-18T13:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的最適輸送と因子化結合（Statistical Optimal Transport via Factored Couplings）</news:title>
   <news:publication_date>2026-05-18T13:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691559</loc>
  <lastmod>2026-05-18T13:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミニバッチ持続性によるSGD高速化（Faster SGD training by minibatch persistency）</news:title>
   <news:publication_date>2026-05-18T13:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691557</loc>
  <lastmod>2026-05-18T12:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトニュクリア・ダイジェットのシミュレーションと核PDF感度（Simulations of photo-nuclear dijets with Pythia 8）</news:title>
   <news:publication_date>2026-05-18T12:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691555</loc>
  <lastmod>2026-05-18T12:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチタスク学習による文の簡易化（Dynamic Multi-Level Multi-Task Learning for Sentence Simplification）</news:title>
   <news:publication_date>2026-05-18T12:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691553</loc>
  <lastmod>2026-05-18T12:21:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォレスト・パッキング：高速並列決定フォレスト（Forest Packing: Fast, Parallel Decision Forests）</news:title>
   <news:publication_date>2026-05-18T12:21:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691551</loc>
  <lastmod>2026-05-18T12:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形観測からの推定を凸最適化で解く実務的示唆（Estimation from Nonlinear Observations via Convex Programming）</news:title>
   <news:publication_date>2026-05-18T12:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691549</loc>
  <lastmod>2026-05-18T12:21:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベース補完のための正準テンソル分解（Canonical Tensor Decomposition for Knowledge Base Completion）</news:title>
   <news:publication_date>2026-05-18T12:21:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691547</loc>
  <lastmod>2026-05-18T12:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし深層マルチフォーカス画像融合（Unsupervised Deep Multi-focus Image Fusion）</news:title>
   <news:publication_date>2026-05-18T12:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691545</loc>
  <lastmod>2026-05-18T12:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知領域へ汎化する方程式学習法（Learning Equations for Extrapolation and Control）</news:title>
   <news:publication_date>2026-05-18T12:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691543</loc>
  <lastmod>2026-05-18T11:29:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点多グラフ埋め込みによる脳ネットワーククラスタリング（Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis）</news:title>
   <news:publication_date>2026-05-18T11:29:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691541</loc>
  <lastmod>2026-05-18T11:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成対抗ネットワークの評価指標に関する実証的研究（An empirical study on evaluation metrics of generative adversarial networks）</news:title>
   <news:publication_date>2026-05-18T11:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691539</loc>
  <lastmod>2026-05-18T11:28:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問に応じたグラフ構造を学習して解釈可能な視覚質問応答を実現する手法（Learning Conditioned Graph Structures for Interpretable Visual Question Answering）</news:title>
   <news:publication_date>2026-05-18T11:28:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691537</loc>
  <lastmod>2026-05-18T11:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オイラー・ラグランジュ系の安定ガウス過程追従制御（Stable Gaussian Process based Tracking Control of Euler-Lagrange Systems）</news:title>
   <news:publication_date>2026-05-18T11:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691535</loc>
  <lastmod>2026-05-18T11:28:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気共鳴スペクトロスコピーの定量化に深層学習を使う（Magnetic Resonance Spectroscopy Quantification using Deep Learning）</news:title>
   <news:publication_date>2026-05-18T11:28:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691533</loc>
  <lastmod>2026-05-18T11:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力推定の適応手法と観察学習への応用（Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations）</news:title>
   <news:publication_date>2026-05-18T11:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691531</loc>
  <lastmod>2026-05-18T11:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間領域デジタル逆伝播のASIC実装と深層学習による色分散フィルタ最適化（ASIC Implementation of Time-Domain Digital Backpropagation with Deep-Learned Chromatic Dispersion Filters）</news:title>
   <news:publication_date>2026-05-18T11:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691529</loc>
  <lastmod>2026-05-18T10:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間チャネル相関ネットワークによる行動分類（Spatio-Temporal Channel Correlation Networks for Action Classification）</news:title>
   <news:publication_date>2026-05-18T10:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691527</loc>
  <lastmod>2026-05-18T10:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TIMIT音素認識における再帰型DNNとアンサンブルの実践（Recurrent DNNs and its Ensembles on the TIMIT Phone Recognition Task）</news:title>
   <news:publication_date>2026-05-18T10:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691525</loc>
  <lastmod>2026-05-18T10:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TIMITにおけるDNNアーキテクチャの比較（A Survey of Recent DNN Architectures on the TIMIT Phone Recognition Task）</news:title>
   <news:publication_date>2026-05-18T10:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691523</loc>
  <lastmod>2026-05-18T10:35:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FRnet-DTI：進化的特徴と構造特徴を組み込んだ深層畳み込みによる薬物–標的相互作用予測（FRnet-DTI: Deep Convolutional Neural Networks with Evolutionary and Structural Features for Drug-Target Interaction）</news:title>
   <news:publication_date>2026-05-18T10:35:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691521</loc>
  <lastmod>2026-05-18T10:35:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FrancyによるGAPの対話的離散数学フレームワーク（Francy - An Interactive Discrete Mathematics Framework for GAP）</news:title>
   <news:publication_date>2026-05-18T10:35:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691519</loc>
  <lastmod>2026-05-18T10:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ混合と対称的識別器が示すGAN訓練の新地平（Mixed batches and symmetric discriminators for GAN training）</news:title>
   <news:publication_date>2026-05-18T10:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691517</loc>
  <lastmod>2026-05-18T10:35:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲルマニウムオンシリコンによるロックインピクセルで屋外対応の高精度3D測距を拓く（Proposal and demonstration of germanium-on-silicon lock-in pixels for indirect time-of-flight based three-dimensional sensing）</news:title>
   <news:publication_date>2026-05-18T10:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691515</loc>
  <lastmod>2026-05-18T09:43:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率単体上の大規模確率的サンプリング（Large-Scale Stochastic Sampling from the Probability Simplex）</news:title>
   <news:publication_date>2026-05-18T09:43:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691513</loc>
  <lastmod>2026-05-18T09:34:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャンク単位の部分フィードバックによる翻訳学習（Learning from Chunk-based Feedback in Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-18T09:34:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691511</loc>
  <lastmod>2026-05-18T09:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行認識のためのCNNベース多モーダル特徴融合（Multimodal feature fusion for CNN-based gait recognition: an empirical comparison）</news:title>
   <news:publication_date>2026-05-18T09:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691509</loc>
  <lastmod>2026-05-18T09:33:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師付きハッシングによる半対ペアクロスビュー検索（Semi-supervised Hashing for Semi-Paired Cross-View Retrieval）</news:title>
   <news:publication_date>2026-05-18T09:33:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691507</loc>
  <lastmod>2026-05-18T09:33:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス対応の汎用補助分類器を組み合わせた生成敵対ネットワーク（Versatile Auxiliary Classifier with Generative Adversarial Network）</news:title>
   <news:publication_date>2026-05-18T09:33:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691505</loc>
  <lastmod>2026-05-18T09:33:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽観測画像のリアルタイム復元を可能にする深層学習（Real-time multiframe blind deconvolution of solar images）</news:title>
   <news:publication_date>2026-05-18T09:33:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691503</loc>
  <lastmod>2026-05-18T09:32:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チューニング時の分散を減らすJ-K-fold交差検証の提案（Using J-K-fold Cross Validation to Reduce Variance When Tuning NLP Models）</news:title>
   <news:publication_date>2026-05-18T09:32:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691501</loc>
  <lastmod>2026-05-18T08:42:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的類似性に基づく特徴学習（Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans）</news:title>
   <news:publication_date>2026-05-18T08:42:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691499</loc>
  <lastmod>2026-05-18T08:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保険不正検知のためのインスタンス単位説明手法（Instance-Level Explanations for Fraud Detection: A Case Study）</news:title>
   <news:publication_date>2026-05-18T08:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691497</loc>
  <lastmod>2026-05-18T08:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FineTagによる細粒度属性認識の軽量化と応用可能性（FineTag: Multi-attribute Classification at Fine-grained Level in Images）</news:title>
   <news:publication_date>2026-05-18T08:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691495</loc>
  <lastmod>2026-05-18T08:31:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNetとZCAに基づく赤外線と可視光画像の融合（Infrared and Visible Image Fusion with ResNet and zero-phase component analysis）</news:title>
   <news:publication_date>2026-05-18T08:31:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691493</loc>
  <lastmod>2026-05-18T08:31:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレアがCME/SEPを伴うかを予測する機械学習（USING MACHINE LEARNING METHODS TO FORECAST IF SOLAR FLARES WILL BE ASSOCIATED WITH CMES AND SEPS）</news:title>
   <news:publication_date>2026-05-18T08:31:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691491</loc>
  <lastmod>2026-05-18T08:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ストリームネットワークによるモダリティ蒸留と行動認識（Modality Distillation with Multiple Stream Networks for Action Recognition）</news:title>
   <news:publication_date>2026-05-18T08:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691489</loc>
  <lastmod>2026-05-18T08:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調的キューイングによる人間-マルチロボット相互作用の改善（Cooperative Queuing Policies for Effective Human-Multi-Robot Interaction）</news:title>
   <news:publication_date>2026-05-18T08:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691487</loc>
  <lastmod>2026-05-18T07:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン線形二次制御 (Online Linear Quadratic Control)</news:title>
   <news:publication_date>2026-05-18T07:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691485</loc>
  <lastmod>2026-05-18T07:39:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き深層畳み込み生成対向ネットワークによる脳–コンピュータインタフェースのデータ拡張（Improving brain computer interface performance by data augmentation with conditional Deep Convolutional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-18T07:39:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691483</loc>
  <lastmod>2026-05-18T07:39:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広域なディスク風モデルが示唆するクエasar構造の再考（Using the Properties of Broad Absorption Line Quasars to Illuminate Quasar Structure）</news:title>
   <news:publication_date>2026-05-18T07:39:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691481</loc>
  <lastmod>2026-05-18T07:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>角膜組織への転移学習における最適なカットオフ層の解析 (Transfer Learning with Human Corneal Tissues: An Analysis of Optimal Cut-Off Layer)</news:title>
   <news:publication_date>2026-05-18T07:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691479</loc>
  <lastmod>2026-05-18T07:38:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率式の簡約による因果推論の実務的意義（Simplifying Probabilistic Expressions in Causal Inference）</news:title>
   <news:publication_date>2026-05-18T07:38:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691477</loc>
  <lastmod>2026-05-18T07:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果効果の同定を枝刈りで改善する（Enhancing Identification of Causal Effects by Pruning）</news:title>
   <news:publication_date>2026-05-18T07:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691475</loc>
  <lastmod>2026-05-18T07:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるモデル更新——Recurrent Meta-learnerを用いた物体追跡の革新 (Learning to Update for Object Tracking with Recurrent Meta-learner)</news:title>
   <news:publication_date>2026-05-18T07:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691473</loc>
  <lastmod>2026-05-18T06:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制限付きボルツマンマシンの入門とレビュー (Restricted Boltzmann Machines: Introduction and Review)</news:title>
   <news:publication_date>2026-05-18T06:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691471</loc>
  <lastmod>2026-05-18T06:46:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>がん転移検出におけるニューラル条件付確率場（Neural Conditional Random Field）</news:title>
   <news:publication_date>2026-05-18T06:46:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691469</loc>
  <lastmod>2026-05-18T06:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーパラメータ最適化が示す真実──IoT分散侵入検知モデルの再現性検証（Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment）</news:title>
   <news:publication_date>2026-05-18T06:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691467</loc>
  <lastmod>2026-05-18T06:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込み永続図の距離歪みについて（On the Metric Distortion of Embedding Persistence Diagrams into separable Hilbert spaces）</news:title>
   <news:publication_date>2026-05-18T06:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691465</loc>
  <lastmod>2026-05-18T06:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール特徴の適応的重み付けによるシーン解析（MoE-SPNet: A Mixture-of-Experts Scene Parsing Network）</news:title>
   <news:publication_date>2026-05-18T06:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691463</loc>
  <lastmod>2026-05-18T06:45:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超対称変換を用いたα核ポテンシャル解析（Analysing supersymmetric transformed α-nucleus potentials with electric-multipole transitions）</news:title>
   <news:publication_date>2026-05-18T06:45:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691461</loc>
  <lastmod>2026-05-18T06:44:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像圧縮センシングのための深層ニューラルネットワークに基づく疎測定行列（Deep Neural Network Based Sparse Measurement Matrix for Image Compressed Sensing）</news:title>
   <news:publication_date>2026-05-18T06:44:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691459</loc>
  <lastmod>2026-05-18T05:54:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VirtualHome：家庭内活動をプログラムでシミュレートする（VirtualHome: Simulating Household Activities via Programs）</news:title>
   <news:publication_date>2026-05-18T05:54:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691457</loc>
  <lastmod>2026-05-18T05:53:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大不変データ摂動による説明手法（Maximally Invariant Data Perturbation as Explanation）</news:title>
   <news:publication_date>2026-05-18T05:53:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691455</loc>
  <lastmod>2026-05-18T05:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像間変換に関する敵対学習の理論解析（Theoretical Analysis of Image-to-Image Translation with Adversarial Learning）</news:title>
   <news:publication_date>2026-05-18T05:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691453</loc>
  <lastmod>2026-05-18T05:52:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Neural Decision Trees（Deep Neural Decision Trees）</news:title>
   <news:publication_date>2026-05-18T05:52:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691451</loc>
  <lastmod>2026-05-18T05:52:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文制約付き双方向非同期アプローチによる感情対話生成（A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation）</news:title>
   <news:publication_date>2026-05-18T05:52:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691449</loc>
  <lastmod>2026-05-18T05:52:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負・凸多項式の最適化と半正定値計画法の扱い（OPTIMIZATION OVER NONNEGATIVE AND CONVEX POLYNOMIALS WITH AND WITHOUT SEMIDEFINITE PROGRAMMING）</news:title>
   <news:publication_date>2026-05-18T05:52:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691447</loc>
  <lastmod>2026-05-18T05:51:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3.5 GHz帯スペクトログラムの深層学習分類（Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing）</news:title>
   <news:publication_date>2026-05-18T05:51:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691445</loc>
  <lastmod>2026-05-18T05:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モード接続による損失ランドスケープ解析（Using Mode Connectivity for Loss Landscape Analysis）</news:title>
   <news:publication_date>2026-05-18T05:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691443</loc>
  <lastmod>2026-05-18T04:51:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的繰り返しの推定（Repetition Estimation）</news:title>
   <news:publication_date>2026-05-18T04:51:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691441</loc>
  <lastmod>2026-05-18T04:50:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Patch-based Iterative Networkによる高速多点ランドマーク局在（Fast Multiple Landmark Localisation Using a Patch-based Iterative Network）</news:title>
   <news:publication_date>2026-05-18T04:50:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691439</loc>
  <lastmod>2026-05-18T04:50:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GroupReduce: ブロック単位の低ランク近似による言語モデル圧縮（GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking）</news:title>
   <news:publication_date>2026-05-18T04:50:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691437</loc>
  <lastmod>2026-05-18T04:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークのデコンボリューションによる細胞検出（Deconvolving Convolutional Neural Network for Cell Detection）</news:title>
   <news:publication_date>2026-05-18T04:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691435</loc>
  <lastmod>2026-05-18T04:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>奇数素数体上のリード・ミューラー符号のバイアス（On the Bias of Reed-Muller Codes over Odd Prime Fields）</news:title>
   <news:publication_date>2026-05-18T04:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691433</loc>
  <lastmod>2026-05-18T04:49:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現畳み込みに向けた遺伝子相互作用グラフの活用（Towards Gene Expression Convolutions using Gene Interaction Graphs）</news:title>
   <news:publication_date>2026-05-18T04:49:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691431</loc>
  <lastmod>2026-05-18T03:58:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重複クラスタリングモデルとOne-Class SVMによる統一的推定（Overlapping Clustering Models, and One (class) SVM to Bind Them All）</news:title>
   <news:publication_date>2026-05-18T03:58:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691429</loc>
  <lastmod>2026-05-18T03:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語ニューラル機械翻訳におけるTransformerとRNNの比較（A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-18T03:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691427</loc>
  <lastmod>2026-05-18T03:57:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な二値評価システムの設計（Designing Optimal Binary Rating Systems）</news:title>
   <news:publication_date>2026-05-18T03:57:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691425</loc>
  <lastmod>2026-05-18T03:56:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外側ハロー衛星のMegaCam調査：光度と構造パラメータ（A MEGACAM SURVEY OF OUTER HALO SATELLITES. III. PHOTOMETRIC AND STRUCTURAL PARAMETERS）</news:title>
   <news:publication_date>2026-05-18T03:56:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691423</loc>
  <lastmod>2026-05-18T03:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メガカムによる銀河ハロー衛星の大規模光学撮像サーベイ（A MEGACAM SURVEY OF HALO SATELLITES）</news:title>
   <news:publication_date>2026-05-18T03:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691421</loc>
  <lastmod>2026-05-18T03:56:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心筋梗塞検出と解釈を行う全畳み込みニューラルネットワーク（Detecting and interpreting myocardial infarction using fully convolutional neural networks）</news:title>
   <news:publication_date>2026-05-18T03:56:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691419</loc>
  <lastmod>2026-05-18T03:56:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数学における証明の読み方・書き方・教え方（Mathematical Proofs 101）</news:title>
   <news:publication_date>2026-05-18T03:56:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691417</loc>
  <lastmod>2026-05-18T03:04:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションと弱ラベル画像からの物体局所化と6次元姿勢推定（Learning Object Localization and 6D Pose Estimation from Simulation and Weakly Labeled Real Images）</news:title>
   <news:publication_date>2026-05-18T03:04:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691415</loc>
  <lastmod>2026-05-18T03:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Tから7T相当のMRIを復元する学習法（Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images）</news:title>
   <news:publication_date>2026-05-18T03:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691413</loc>
  <lastmod>2026-05-18T03:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正規分布とIsing無向グラフィカルモデルの最小最大学習率（The minimax learning rates of normal and Ising undirected graphical models）</news:title>
   <news:publication_date>2026-05-18T03:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691411</loc>
  <lastmod>2026-05-18T03:02:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロモスフェリック凝縮と磁場の可視化（Chromospheric condensations and magnetic field in a C3.6-class flare studied via He i D3 spectro-polarimetry）</news:title>
   <news:publication_date>2026-05-18T03:02:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691409</loc>
  <lastmod>2026-05-18T03:02:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レビューから学ぶ分散表現と協調フィルタリングの強化（Learning Distributed Representations from Reviews for Collaborative Filtering）</news:title>
   <news:publication_date>2026-05-18T03:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691407</loc>
  <lastmod>2026-05-18T03:02:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆強化学習の総説（A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress）</news:title>
   <news:publication_date>2026-05-18T03:02:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691405</loc>
  <lastmod>2026-05-18T03:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織学的ハッシュとクラス固有マンifold学習を用いた識別的アンサンブルによる乳癌多クラス分類（Diving Deep onto Discriminative Ensemble of Histological Hashing &amp;amp; Class-Specific Manifold Learning）</news:title>
   <news:publication_date>2026-05-18T03:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691403</loc>
  <lastmod>2026-05-18T02:10:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続変数量子ニューラルネットワーク（Continuous-variable quantum neural networks）</news:title>
   <news:publication_date>2026-05-18T02:10:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691401</loc>
  <lastmod>2026-05-18T02:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対流核を持つ星の重力モードによる前向き星震学モデリング（Forward asteroseismic modeling of stars with a convective core from gravity-mode oscillations）</news:title>
   <news:publication_date>2026-05-18T02:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691399</loc>
  <lastmod>2026-05-18T02:09:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ波長対応の機械学習によるサブミリ波銀河同定法 (A MACHINE-LEARNING METHOD FOR IDENTIFYING MULTI-WAVELENGTH COUNTERPARTS OF SUBMILLIMETER GALAXIES)</news:title>
   <news:publication_date>2026-05-18T02:09:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691397</loc>
  <lastmod>2026-05-18T02:08:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定アルゴリズムのためのインスタンス依存事前分布を用いたPAC-Bayes境界（PAC-Bayes bounds for stable algorithms with instance-dependent priors）</news:title>
   <news:publication_date>2026-05-18T02:08:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691395</loc>
  <lastmod>2026-05-18T02:08:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>渦巻銀河M101の外縁円盤とハローにおける恒星集団（STELLAR POPULATIONS IN THE OUTER DISK AND HALO OF THE SPIRAL GALAXY M101）</news:title>
   <news:publication_date>2026-05-18T02:08:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691393</loc>
  <lastmod>2026-05-18T02:08:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移クラスター環境の活動と休止を読み解く（DECIPHERING THE ACTIVITY AND QUIESCENCE OF HIGH-REDSHIFT CLUSTER ENVIRONMENTS）</news:title>
   <news:publication_date>2026-05-18T02:08:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691391</loc>
  <lastmod>2026-05-18T02:08:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオデータを用いた橋梁部材の自動認識（Automated Bridge Component Recognition using Video Data）</news:title>
   <news:publication_date>2026-05-18T02:08:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691389</loc>
  <lastmod>2026-05-18T01:16:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移の静止銀河における回転支持の直接測定（Resolving Quiescent Galaxies at z ≳2: II. Direct Measures of Rotational Support）</news:title>
   <news:publication_date>2026-05-18T01:16:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691387</loc>
  <lastmod>2026-05-18T01:16:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹腔鏡ワークフロー解析のための時間的一貫性に基づく自己教師あり学習（Temporal coherence-based self-supervised learning for laparoscopic workflow analysis）</news:title>
   <news:publication_date>2026-05-18T01:16:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691385</loc>
  <lastmod>2026-05-18T01:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚のドリフトは仮説選択ではなく誤差の融合で説明できる（Drifting perceptual patterns suggest prediction errors fusion rather than hypothesis selection）</news:title>
   <news:publication_date>2026-05-18T01:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691383</loc>
  <lastmod>2026-05-18T01:15:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所ナッシュ均衡を超えて（Beyond Local Nash Equilibria for Adversarial Networks）</news:title>
   <news:publication_date>2026-05-18T01:15:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691381</loc>
  <lastmod>2026-05-18T01:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の時空間表現による自動的な痛み強度推定（Deep Spatiotemporal Representation of the Face for Automatic Pain Intensity Estimation）</news:title>
   <news:publication_date>2026-05-18T01:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691379</loc>
  <lastmod>2026-05-18T01:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なほぼ厳密マッチングによる因果推論（Interpretable Almost-Matching Exactly for Causal Inference）</news:title>
   <news:publication_date>2026-05-18T01:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691377</loc>
  <lastmod>2026-05-18T01:15:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模評価フレームワークによるEEG深層学習の実証（A large-scale evaluation framework for EEG deep learning architectures）</news:title>
   <news:publication_date>2026-05-18T01:15:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691375</loc>
  <lastmod>2026-05-18T00:24:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均処置効果の頑健な推定：Outcome Highly Adaptive Lassoの提案（Robust inference on the average treatment effect using the outcome highly adaptive lasso）</news:title>
   <news:publication_date>2026-05-18T00:24:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691373</loc>
  <lastmod>2026-05-18T00:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BinGANによるコンパクトな2値特徴量学習（BinGAN: Learning Compact Binary Descriptors with a Regularized GAN）</news:title>
   <news:publication_date>2026-05-18T00:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691371</loc>
  <lastmod>2026-05-18T00:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的イントネーション輪郭の重み付き重ね合わせモデル（A Weighted Superposition of Functional Contours Model for Modelling Contextual Prominence of Elementary Prosodic Contours）</news:title>
   <news:publication_date>2026-05-18T00:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691369</loc>
  <lastmod>2026-05-18T00:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な深層学習による音楽オンセット検出の実装指針（TOWARDS AN EFFICIENT DEEP LEARNING MODEL FOR MUSICAL ONSET DETECTION）</news:title>
   <news:publication_date>2026-05-18T00:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691367</loc>
  <lastmod>2026-05-18T00:23:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意管理システムの概観（A Survey of Attention Management Systems in Ubiquitous Computing Environments）</news:title>
   <news:publication_date>2026-05-18T00:23:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691365</loc>
  <lastmod>2026-05-18T00:23:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階フィッシャー独立性検定による多変量依存の検出（Multiscale Fisher’s Independence Test for Multivariate Dependence）</news:title>
   <news:publication_date>2026-05-18T00:23:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691363</loc>
  <lastmod>2026-05-18T00:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆クリストッフェル関数をカーネル化した異常検知（Kernel-based Outlier Detection using the Inverse Christoffel Function）</news:title>
   <news:publication_date>2026-05-18T00:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691361</loc>
  <lastmod>2026-05-17T23:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール化が鍵となる不変関係推論（Modularity Matters: Learning Invariant Relational Reasoning Tasks）</news:title>
   <news:publication_date>2026-05-17T23:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691359</loc>
  <lastmod>2026-05-17T23:31:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的勾配法の一般化ギャップを埋める（Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-17T23:31:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691357</loc>
  <lastmod>2026-05-17T23:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠方銀河の分子ガスとALMA観測（Molecular gas in distant galaxies from ALMA studies）</news:title>
   <news:publication_date>2026-05-17T23:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691355</loc>
  <lastmod>2026-05-17T23:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Eloレーティングに学習効果を組み込む数理モデル（BOLTZMANN AND FOKKER-PLANCK EQUATIONS MODELLING THE ELO RATING SYSTEM WITH LEARNING EFFECTS）</news:title>
   <news:publication_date>2026-05-17T23:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691353</loc>
  <lastmod>2026-05-17T23:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチインストゥルメントドラムの自動転写（TOWARDS MULTI-INSTRUMENT DRUM TRANSCRIPTION）</news:title>
   <news:publication_date>2026-05-17T23:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691351</loc>
  <lastmod>2026-05-17T23:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バスケットボールにおけるゲーム成功の社会ネットワーク指標（SMOGS: Social Network Metrics of Game Success）</news:title>
   <news:publication_date>2026-05-17T23:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691349</loc>
  <lastmod>2026-05-17T23:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングパターンのエンドツーエンド学習（End-to-end Sampling Patterns）</news:title>
   <news:publication_date>2026-05-17T23:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691347</loc>
  <lastmod>2026-05-17T22:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声感情認識を強化するGANの利用（On Enhancing Speech Emotion Recognition using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-17T22:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691345</loc>
  <lastmod>2026-05-17T22:39:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Banach空間におけるWasserstein GANの拡張（Banach Wasserstein GAN）</news:title>
   <news:publication_date>2026-05-17T22:39:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691343</loc>
  <lastmod>2026-05-17T22:39:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッシブなダウンリンク指標からのアップリンク送信電力予測（Machine Learning Based Uplink Transmission Power Prediction for LTE and Upcoming 5G Networks using Passive Downlink Indicators）</news:title>
   <news:publication_date>2026-05-17T22:39:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691341</loc>
  <lastmod>2026-05-17T22:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>比較に基づくランダムフォレスト（Comparison-Based Random Forests）</news:title>
   <news:publication_date>2026-05-17T22:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691339</loc>
  <lastmod>2026-05-17T22:38:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常データからの逐次学習の評価と特徴付け（Evaluating and Characterizing Incremental Learning from Non-Stationary Data）</news:title>
   <news:publication_date>2026-05-17T22:38:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691337</loc>
  <lastmod>2026-05-17T22:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDSS画像からの光学的赤方偏移推定（Photometric redshifts from SDSS images using a Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-17T22:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691335</loc>
  <lastmod>2026-05-17T22:38:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IC 5070の変光性：深い周期性の食現象を示す若い星二例（Variability in IC 5070: two young stars with deep recurring eclipses）</news:title>
   <news:publication_date>2026-05-17T22:38:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691333</loc>
  <lastmod>2026-05-17T21:47:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習における圧縮勾配の理論と実践（Distributed Learning with Compressed Gradients）</news:title>
   <news:publication_date>2026-05-17T21:47:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691331</loc>
  <lastmod>2026-05-17T21:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習における不確実性と共同表現（Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning）</news:title>
   <news:publication_date>2026-05-17T21:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691329</loc>
  <lastmod>2026-05-17T21:38:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチターゲットフィルタリングのための深層リカレントニューラルネットワーク (Deep Recurrent Neural Network for Multi-target Filtering)</news:title>
   <news:publication_date>2026-05-17T21:38:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691327</loc>
  <lastmod>2026-05-17T21:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックなトピックモデルとニューラル推論の統合（Nonparametric Topic Modeling with Neural Inference）</news:title>
   <news:publication_date>2026-05-17T21:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691325</loc>
  <lastmod>2026-05-17T21:38:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D形状からの微分可能レンダリングを学ぶ（RenderNet: A deep convolutional network for differentiable rendering from 3D shapes）</news:title>
   <news:publication_date>2026-05-17T21:38:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691323</loc>
  <lastmod>2026-05-17T21:37:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分スパースベイズ順序回帰（Incremental Sparse Bayesian Ordinal Regression）</news:title>
   <news:publication_date>2026-05-17T21:37:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691321</loc>
  <lastmod>2026-05-17T21:37:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続的に学ぶロボット設計の視点：倒れることから学ぶ（Learning from Outside the Viability Kernel: Why we Should Build Robots that can Fall With Grace）</news:title>
   <news:publication_date>2026-05-17T21:37:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691319</loc>
  <lastmod>2026-05-17T20:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リカレントニューラルネットワークによる音楽嗜好進化のモデリング（Modeling Musical Taste Evolution with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-17T20:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691317</loc>
  <lastmod>2026-05-17T20:46:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実数値を保持するシンプルなリザバー型ワーキングメモリモデル（A Simple Reservoir Model of Working Memory with Real Values）</news:title>
   <news:publication_date>2026-05-17T20:46:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691315</loc>
  <lastmod>2026-05-17T20:46:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全な対のデータに対する代入法の落とし穴（A cautionary tale on using imputation methods for inference in matched pairs design）</news:title>
   <news:publication_date>2026-05-17T20:46:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691313</loc>
  <lastmod>2026-05-17T20:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートホーム向け暗号化パケット分類の階層的アプローチ（A Hierarchical Approach to Encrypted Data Packet Classification in Smart Home Gateways）</news:title>
   <news:publication_date>2026-05-17T20:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691311</loc>
  <lastmod>2026-05-17T20:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報自己符号化ファミリ：潜在変数生成モデルに対するラグランジュ的視点（The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models）</news:title>
   <news:publication_date>2026-05-17T20:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691309</loc>
  <lastmod>2026-05-17T20:45:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半結合ユニットによるLSTM・Highwayネットの効率的ゲーティング（Semi-tied Units for Efficient Gating in LSTM and Highway Networks）</news:title>
   <news:publication_date>2026-05-17T20:45:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691307</loc>
  <lastmod>2026-05-17T20:45:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心音データに対する転移学習＋表現学習＋教師あり学習のアンサンブル（An Ensemble of Transfer, Semi-supervised and Supervised Learning Methods for Pathological Heart Sound Classification）</news:title>
   <news:publication_date>2026-05-17T20:45:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691305</loc>
  <lastmod>2026-05-17T19:54:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>好奇心とエンパワーメント駆動強化学習の統合的実装戦略（A unified strategy for implementing curiosity and empowerment driven reinforcement learning）</news:title>
   <news:publication_date>2026-05-17T19:54:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691303</loc>
  <lastmod>2026-05-17T19:54:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>送電網コントローラの異常検知における時系列深層学習の強化（Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning）</news:title>
   <news:publication_date>2026-05-17T19:54:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691301</loc>
  <lastmod>2026-05-17T19:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conditional Affordance Learning（Conditional Affordance Learning for Driving in Urban Environments）</news:title>
   <news:publication_date>2026-05-17T19:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691299</loc>
  <lastmod>2026-05-17T19:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tc と Tb^c の圏は互いに決定する（THE CATEGORIES Tc AND Tb^c DETERMINE EACH OTHER）</news:title>
   <news:publication_date>2026-05-17T19:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691297</loc>
  <lastmod>2026-05-17T19:53:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散医療データにおけるプライバシー保護分析（Privacy Preserving Analytics on Distributed Medical Data）</news:title>
   <news:publication_date>2026-05-17T19:53:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691295</loc>
  <lastmod>2026-05-17T19:53:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフと記述文の共同学習による多言語エンティティ整列（Co-training Embeddings of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment）</news:title>
   <news:publication_date>2026-05-17T19:53:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691293</loc>
  <lastmod>2026-05-17T19:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェントにおけるポリシー表現学習（Learning Policy Representations in Multiagent Systems）</news:title>
   <news:publication_date>2026-05-17T19:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691291</loc>
  <lastmod>2026-05-17T19:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの高速凸プルーニング（Fast Convex Pruning of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-17T19:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691289</loc>
  <lastmod>2026-05-17T19:01:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上のラベル変化をオンラインで予測する手法（Online Prediction of Switching Graph Labelings with Cluster Specialists）</news:title>
   <news:publication_date>2026-05-17T19:01:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691287</loc>
  <lastmod>2026-05-17T19:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多殻拡散強調MRIのq空間を小さく表現する学習（Learning compact q-space representations for multi-shell diffusion-weighted MRI）</news:title>
   <news:publication_date>2026-05-17T19:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691285</loc>
  <lastmod>2026-05-17T19:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜疾患の自動分類のための新規ハイブリッド機械学習モデル（A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases）</news:title>
   <news:publication_date>2026-05-17T19:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691283</loc>
  <lastmod>2026-05-17T19:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプション評価の学習的判定法（Learning to Evaluate Image Captioning）</news:title>
   <news:publication_date>2026-05-17T19:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691281</loc>
  <lastmod>2026-05-17T18:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Orliczノルムによる部分空間埋め込みと線形回帰（Subspace Embedding and Linear Regression with Orlicz Norm）</news:title>
   <news:publication_date>2026-05-17T18:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691279</loc>
  <lastmod>2026-05-17T18:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Image Priorを用いた圧縮センシングと学習型正則化（Compressed Sensing with Deep Image Prior and Learned Regularization）</news:title>
   <news:publication_date>2026-05-17T18:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691277</loc>
  <lastmod>2026-05-17T18:08:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速追跡を実現するマルチカーネル相関フィルタの提案（High-speed Tracking with Multi-kernel Correlation Filters）</news:title>
   <news:publication_date>2026-05-17T18:08:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691275</loc>
  <lastmod>2026-05-17T18:07:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳画像から認知障害を予測するための特徴学習と分類（Feature Learning and Classification in Neuroimaging: Predicting Cognitive Impairment from Magnetic Resonance Imaging）</news:title>
   <news:publication_date>2026-05-17T18:07:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691273</loc>
  <lastmod>2026-05-17T18:07:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話の意味的一貫性を測る—対話の文脈理解を数値化する手法（Measuring Semantic Coherence of a Conversation）</news:title>
   <news:publication_date>2026-05-17T18:07:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691271</loc>
  <lastmod>2026-05-17T18:06:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多成分学習によるタンパク質二次構造予測の実践的理解（MCP: a Multi-Component learning machine to Predict protein secondary structure）</news:title>
   <news:publication_date>2026-05-17T18:06:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691269</loc>
  <lastmod>2026-05-17T18:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路計画を安定化するゲーティッドな設計（Gated Path Planning Networks）</news:title>
   <news:publication_date>2026-05-17T18:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691267</loc>
  <lastmod>2026-05-17T18:06:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク関連オブジェクトの発見と分類（Task-Relevant Object Discovery and Categorization for Playing First-person Shooter Games）</news:title>
   <news:publication_date>2026-05-17T18:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691265</loc>
  <lastmod>2026-05-17T18:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量LSTMによる説明可能な時系列予測（Multi-variable LSTM neural network for autoregressive exogenous model）</news:title>
   <news:publication_date>2026-05-17T18:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691263</loc>
  <lastmod>2026-05-17T17:15:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StegNetが変えた「画像ステガノグラフィの常識」—高密度隠蔽を可能にした深層畳み込みネットワーク（StegNet: Mega Image Steganography Capacity with Deep Convolutional Network）</news:title>
   <news:publication_date>2026-05-17T17:15:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691261</loc>
  <lastmod>2026-05-17T17:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多面体理論が深層学習に与える示唆（How Could Polyhedral Theory Harness Deep Learning?）</news:title>
   <news:publication_date>2026-05-17T17:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691259</loc>
  <lastmod>2026-05-17T17:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均一ポアソン過程のパラメータ推定におけるモーメント法と多段階最尤推定（Method of Moments Estimators and Multu-step MLE for Poisson Processes）</news:title>
   <news:publication_date>2026-05-17T17:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691257</loc>
  <lastmod>2026-05-17T17:05:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>測地線凸最適化（Geodesic Convex Optimization: Differentiation on Manifolds, Geodesics, and Convexity）</news:title>
   <news:publication_date>2026-05-17T17:05:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691255</loc>
  <lastmod>2026-05-17T17:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUの初期化と動的等方性の達成（Initialization of ReLUs for Dynamical Isometry）</news:title>
   <news:publication_date>2026-05-17T17:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691253</loc>
  <lastmod>2026-05-17T17:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語の文字情報を活かした語彙セメム予測（Incorporating Chinese Characters of Words for Lexical Sememe Prediction）</news:title>
   <news:publication_date>2026-05-17T17:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691251</loc>
  <lastmod>2026-05-17T17:04:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソル同士の積を扱うツールボックス（Tensor-Tensor Product Toolbox）</news:title>
   <news:publication_date>2026-05-17T17:04:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691249</loc>
  <lastmod>2026-05-17T16:13:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StarGOによる銀河ハロー星の起源同定法（STARGO: A NEW METHOD TO IDENTIFY THE GALACTIC ORIGINS OF HALO STARS）</news:title>
   <news:publication_date>2026-05-17T16:13:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691247</loc>
  <lastmod>2026-05-17T16:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Forward-Backward 分割法のQ線形収束と Lasso 最適解の一意性（On the Q-linear convergence of forward-backward splitting method and uniqueness of optimal solution to Lasso）</news:title>
   <news:publication_date>2026-05-17T16:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691245</loc>
  <lastmod>2026-05-17T16:12:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カバーソングの類推による合成（Cover Song Synthesis by Analogy）</news:title>
   <news:publication_date>2026-05-17T16:12:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691243</loc>
  <lastmod>2026-05-17T16:12:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテから学ぶ治療レジメン（Learning Treatment Regimens from Electronic Medical Records）</news:title>
   <news:publication_date>2026-05-17T16:12:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691241</loc>
  <lastmod>2026-05-17T16:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラプラシアン平滑化勾配降下法 (Laplacian Smooth Gradient Descent)</news:title>
   <news:publication_date>2026-05-17T16:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691239</loc>
  <lastmod>2026-05-17T16:11:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似サブモジュラ関数と実務的な性能保証（Approximate Submodular Functions and Performance Guarantees）</news:title>
   <news:publication_date>2026-05-17T16:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691237</loc>
  <lastmod>2026-05-17T16:11:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>In situ TensorViewによる畳み込みニューラルネットワークのインサイチュ可視化（In situ TensorView: In situ Visualization of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-17T16:11:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691235</loc>
  <lastmod>2026-05-17T15:19:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>理由が正しければ結果も正しい（Right for the Right Reason: Training Agnostic Networks）</news:title>
   <news:publication_date>2026-05-17T15:19:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691233</loc>
  <lastmod>2026-05-17T15:19:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観と幾何の分離を行う変形生成器ネットワーク（Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry）</news:title>
   <news:publication_date>2026-05-17T15:19:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691231</loc>
  <lastmod>2026-05-17T15:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな閾値回路に対する平均事例下の下界と効率的充足可能性アルゴリズム（Average-Case Lower Bounds and Satisfiability Algorithms for Small Threshold Circuits）</news:title>
   <news:publication_date>2026-05-17T15:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691229</loc>
  <lastmod>2026-05-17T15:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-17T15:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691227</loc>
  <lastmod>2026-05-17T15:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在畳み込みモデル（LATENT CONVOLUTIONAL MODELS）</news:title>
   <news:publication_date>2026-05-17T15:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691225</loc>
  <lastmod>2026-05-17T15:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師あり二流アーキテクチャによる行動認識の革新（Two Stream Self-Supervised Learning for Action Recognition）</news:title>
   <news:publication_date>2026-05-17T15:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691223</loc>
  <lastmod>2026-05-17T15:17:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピー講義 第I部 (Lectures on Entropy. Part I)</news:title>
   <news:publication_date>2026-05-17T15:17:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>