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   <news:title>量子回路の学習をハイブリッドで行う時代が来た（Training of Quantum Circuits on a Hybrid Quantum Computer）</news:title>
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   <news:title>天文学における転移学習の新しいパラダイム（Transfer Learning in Astronomy: A New Machine-Learning Paradigm）</news:title>
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    <news:language>ja</news:language>
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   <news:title>形式概念体系における関連属性の定義（Relevant Attributes in Formal Contexts）</news:title>
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    <news:language>ja</news:language>
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   <news:title>任意の物体を動かす深層モーション転送（Animating Arbitrary Objects via Deep Motion Transfer）</news:title>
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    <news:language>ja</news:language>
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   <news:title>分散型意思決定とマルチタスクネットワーク（Decentralized Decision-Making Over Multi-Task Networks）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ドメイン適応の一般的アプローチ（A General Approach to Domain Adaptation with Applications in Astronomy）</news:title>
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   <news:title>銀河団コアにおける（未）覆い隠された星形成の抑制の定量化 (Quantifying the suppression of the (un)-obscured star formation in galaxy cluster cores at 0.2≲z≲0.9)</news:title>
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    <news:language>ja</news:language>
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   <news:title>回転不変な指数族主成分分析：Steerable ePCA（Steerable ePCA: Rotationally Invariant Exponential Family PCA）</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>量子ホール系における準正準モードとホーキング・アンルン効果（Quasinormal Modes and Hawking-Unruh effect in Quantum Hall Systems）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T06:29:29Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>サンプリング比を下げて推定数を増やすことでバギングがまばら回帰で改善する（Reducing Sampling Ratios and Increasing Number of Estimates Improve Bagging in Sparse Regression）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T05:38:03Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>限られた注釈データでのラベル伝播のための深層距離学習転移（Deep Metric Transfer for Label Propagation with Limited Annotated Data）</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>論文のゲシュタルトで採否を判定する手法（Deep Paper Gestalt）</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>最小情報完全測定の多様性（The Varieties of Minimal Tomographically Complete Measurements）</news:title>
   <news:publication_date>2026-07-20T05:37:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T05:36:55Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>特別イベント時の公共交通利用を分解するベイズ加法モデル（A Bayesian additive model for understanding public transport usage in special events）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T05:36:47Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>動的ジェットベトーを用いた重いニュートリノ探索（Heavy Neutrinos with Dynamic Jet Vetoes: Multilepton Searches at √s = 14, 27, and 100 TeV）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T05:36:29Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>地下構造解析を視覚信号処理の視点で再定義する（Subsurface Structure Analysis Using Computational Interpretation and Learning: A Visual Signal Processing Perspective）</news:title>
   <news:publication_date>2026-07-20T05:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T05:36:15Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>クラウドソース交通データの欠損補完に対する多出力ガウス過程の提案（Multi-output Gaussian processes for crowdsourced traffic data imputation）</news:title>
   <news:publication_date>2026-07-20T05:36:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T04:45:03Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>単純なフーリエ構造を持つ信号の普遍的サンプリング法（A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms）</news:title>
   <news:publication_date>2026-07-20T04:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T04:44:44Z</lastmod>
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    <news:language>ja</news:language>
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   <news:title>RNNが暗黙のテンソル積表現を実装している（RNNs Implicitly Implement Tensor-Product Representations）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T04:44:32Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大規模クラウドソース交通データにおける時間変動する不確実性モデル（Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data）</news:title>
   <news:publication_date>2026-07-20T04:44:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T04:44:09Z</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>NASAと技術的痕跡（NASA AND THE SEARCH FOR TECHNOSIGNATURES）</news:title>
   <news:publication_date>2026-07-20T04:44:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T04:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>切削工程の力測定を用いたリアルタイム異常検知手法の評価（An Evaluation of Methods for Real-Time Anomaly Detection using Force Measurements from the Turning Process）</news:title>
   <news:publication_date>2026-07-20T04:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T04:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>高次元共変量バランス化傾向スコアによる因果効果の頑健推定 (Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score)</news:title>
   <news:publication_date>2026-07-20T04:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T04:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野生のバグ修正パッチを学習する実証研究（An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-20T04:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T03:52:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトコンダクティブヒーターによる大規模シリコンフォトニックリング共振器制御（Photoconductive heaters enable control of large-scale silicon photonic ring resonator circuits）</news:title>
   <news:publication_date>2026-07-20T03:52:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T03:52:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現データからの癌検出とタイプ分類を促進する手法（A Method to Facilitate Cancer Detection and Type Classification from Gene Expression Data using a Deep Autoencoder and Neural Network）</news:title>
   <news:publication_date>2026-07-20T03:52:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/713810</loc>
  <lastmod>2026-07-20T03:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の物体を説明する大規模ベンチマーク：nocaps（nocaps: novel object captioning at scale）</news:title>
   <news:publication_date>2026-07-20T03:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/713808</loc>
  <lastmod>2026-07-20T03:51:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーティリティ規模太陽光発電所の自動検査（Automatic Inspection of Utility Scale Solar Power Plants using Deep Learning）</news:title>
   <news:publication_date>2026-07-20T03:51:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T03:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>レーザー励起シリコンの自己学習型解析間原子ポテンシャル（Self-learning analytical interatomic potential describing laser-excited silicon）</news:title>
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   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/713804</loc>
  <lastmod>2026-07-20T03:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数結合論に基づく深層手法による偏微分方程式解推定（Deep Theory of Functional Connections: A New Method for Estimating the Solutions of PDEs）</news:title>
   <news:publication_date>2026-07-20T03:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-20T03:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠赤外/サブミリ波検出器向けフォノニックフィルタ構造の作製（Fabrication of phononic filter structures for far-IR/sub-mm detector applications）</news:title>
   <news:publication_date>2026-07-20T03:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/713800</loc>
  <lastmod>2026-07-20T02:59:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAPS中性子飛行時間チャッパースペクトロメータのアップグレード（Upgrade to the MAPS neutron time-of-flight chopper spectrometer）</news:title>
   <news:publication_date>2026-07-20T02:59:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713798</loc>
  <lastmod>2026-07-20T02:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子軌道エネルギー予測における化学的多様性とKRRの実務的示唆（Chemical diversity in molecular orbital energy predictions with kernel ridge regression）</news:title>
   <news:publication_date>2026-07-20T02:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713796</loc>
  <lastmod>2026-07-20T02:59:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像における多臓器解析の計算解剖学（Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review）</news:title>
   <news:publication_date>2026-07-20T02:59:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713794</loc>
  <lastmod>2026-07-20T02:59:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンコーダ・デコーダによる敵対的信号デノイジング（Adversarial Signal Denoising with Encoder-Decoder Networks）</news:title>
   <news:publication_date>2026-07-20T02:59:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713792</loc>
  <lastmod>2026-07-20T02:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUで学ぶ因果構造学習の大幅高速化（cuPC: CUDA-based Parallel PC Algorithm for Causal Structure Learning on GPU）</news:title>
   <news:publication_date>2026-07-20T02:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713790</loc>
  <lastmod>2026-07-20T02:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次アルゴリズムは O(1/k) より速く収束する（First-Order Algorithms Converge Faster than O(1/k) on Convex Problems）</news:title>
   <news:publication_date>2026-07-20T02:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713788</loc>
  <lastmod>2026-07-20T02:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の星形成分布が示す「内部での強化と抑制」──Main Sequence 上下で変わる星生成の局所性（Spatial distribution of stellar mass and star formation activity at 0.2</news:title>
   <news:publication_date>2026-07-20T02:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713786</loc>
  <lastmod>2026-07-20T02:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性に基づく凝集型階層クラスタリング（Reliable Agglomerative Clustering）</news:title>
   <news:publication_date>2026-07-20T02:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713784</loc>
  <lastmod>2026-07-20T02:07:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス内分割によるワンクラス特徴学習（One-Class Feature Learning Using Intra-Class Splitting）</news:title>
   <news:publication_date>2026-07-20T02:07:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713782</loc>
  <lastmod>2026-07-20T02:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による量子誤り訂正コードの最適化（Optimizing Quantum Error Correction Codes with Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-20T02:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713780</loc>
  <lastmod>2026-07-20T02:06:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ内連想処理によるDNN推論加速 AIDA（AIDA: Associative DNN Inference Accelerator）</news:title>
   <news:publication_date>2026-07-20T02:06:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713778</loc>
  <lastmod>2026-07-20T02:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子照射後の深掘り型APDの時間計測性能（Deep Diffused APDs for Charged Particle Timing Applications: Performance after Neutron Irradiation）</news:title>
   <news:publication_date>2026-07-20T02:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713776</loc>
  <lastmod>2026-07-20T02:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな顔に注目する顔検出の設計（SFA: Small Faces Attention Face Detector）</news:title>
   <news:publication_date>2026-07-20T02:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713774</loc>
  <lastmod>2026-07-20T02:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚効果を真似て学ぶ教師なしメタ学習による図-地分割（Unsupervised Meta-learning of Figure-Ground Segmentation via Imitating Visual Effects）</news:title>
   <news:publication_date>2026-07-20T02:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713772</loc>
  <lastmod>2026-07-20T01:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模混合データフレームのための低ランク＋スパース加法モデル（Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames）</news:title>
   <news:publication_date>2026-07-20T01:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713770</loc>
  <lastmod>2026-07-20T01:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習を考慮した問題類似度の新指標（Kappa Learning: A New Method for Measuring Similarity Between Educational Items Using Performance Data）</news:title>
   <news:publication_date>2026-07-20T01:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713768</loc>
  <lastmod>2026-07-20T01:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列異常検知における深層フィードフォワードネットワークの実用性（Feedforward Neural Network for Time Series Anomaly Detection）</news:title>
   <news:publication_date>2026-07-20T01:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713766</loc>
  <lastmod>2026-07-20T01:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形多様体上の動的系のモデル縮約と深層畳み込みオートエンコーダ（Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders）</news:title>
   <news:publication_date>2026-07-20T01:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713764</loc>
  <lastmod>2026-07-20T01:13:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークのデータ不要型自動加速（Data-free Automatic Acceleration of Convolutional Networks）</news:title>
   <news:publication_date>2026-07-20T01:13:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713762</loc>
  <lastmod>2026-07-20T01:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化動的価格設定の原始双対学習アルゴリズム（A Primal-dual Learning Algorithm for Personalized Dynamic Pricing with an Inventory Constraint）</news:title>
   <news:publication_date>2026-07-20T01:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713760</loc>
  <lastmod>2026-07-20T01:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SfMLearner++: Monocular DepthとEgo-Motionを幾何学的制約で学ぶ（SfMLearner++: Learning Monocular Depth &amp;amp; Ego-Motion using Meaningful Geometric Constraints）</news:title>
   <news:publication_date>2026-07-20T01:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713758</loc>
  <lastmod>2026-07-20T00:20:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項式NARXモデルの構造選択における2次元粒子群最適化（Structure Selection of Polynomial NARX Models using Two Dimensional (2D) Particle Swarms）</news:title>
   <news:publication_date>2026-07-20T00:20:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713756</loc>
  <lastmod>2026-07-20T00:20:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2.5Dを用いた多GPU実装によるCT画像再構成の深層学習（2.5D DEEP LEARNING FOR CT IMAGE RECONSTRUCTION USING A MULTI-GPU IMPLEMENTATION）</news:title>
   <news:publication_date>2026-07-20T00:20:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713754</loc>
  <lastmod>2026-07-20T00:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期価格予測のための板情報特徴量調査（Investigating Limit Order Book Characteristics for Short Term Price Prediction: a Machine Learning Approach）</news:title>
   <news:publication_date>2026-07-20T00:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713752</loc>
  <lastmod>2026-07-20T00:19:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4つの低赤shift銀河団のダークマター分布（Dark Matter Distribution of Four Low-z Clusters of Galaxies）</news:title>
   <news:publication_date>2026-07-20T00:19:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713750</loc>
  <lastmod>2026-07-20T00:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深在塩水帯における二酸化炭素の対流溶解の実験的洞察（Convective dissolution of carbon dioxide in deep saline aquifers）</news:title>
   <news:publication_date>2026-07-20T00:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713748</loc>
  <lastmod>2026-07-20T00:19:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブ画像編集のための逐次注意GAN（Sequential Attention GAN for Interactive Image Editing）</news:title>
   <news:publication_date>2026-07-20T00:19:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713746</loc>
  <lastmod>2026-07-20T00:18:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト性が深層学習と出会う：自己教師ありエゴモーションのエンドツーエンドハイブリッドパイプライン（Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion）</news:title>
   <news:publication_date>2026-07-20T00:18:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713744</loc>
  <lastmod>2026-07-19T23:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価値敏感な学習分析設計の方向性（Towards Value-Sensitive Learning Analytics Design）</news:title>
   <news:publication_date>2026-07-19T23:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713742</loc>
  <lastmod>2026-07-19T23:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代数的グラフ学習によるタンパク質—リガンド結合自由エネルギー予測（Algebraic graph learning of protein-ligand binding affinity）</news:title>
   <news:publication_date>2026-07-19T23:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713740</loc>
  <lastmod>2026-07-19T23:24:57Z</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とマルチモーダルアーティスト埋め込みによる歌詞生成（Generating lyrics with variational autoencoder and multi-modal artist embeddings）</news:title>
   <news:publication_date>2026-07-19T23:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713738</loc>
  <lastmod>2026-07-19T23:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的信念改訂と資源制約：論理を幾何学として捉える（Iterated Belief Revision Under Resource Constraints: Logic as Geometry）</news:title>
   <news:publication_date>2026-07-19T23:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713736</loc>
  <lastmod>2026-07-19T23:24:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化と低精度化の同時最適化（SQuantizer: Simultaneous Learning for Both Sparse and Low-precision Neural Networks）</news:title>
   <news:publication_date>2026-07-19T23:24:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713734</loc>
  <lastmod>2026-07-19T23:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NeuralWarp：時系列類似度を再定義するワーピングネットワーク（NeuralWarp: Time-Series Similarity with Warping Networks）</news:title>
   <news:publication_date>2026-07-19T23:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713732</loc>
  <lastmod>2026-07-19T23:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導関数を使わない方策最適化の理論的保証（Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems）</news:title>
   <news:publication_date>2026-07-19T23:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713730</loc>
  <lastmod>2026-07-19T22:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TD正則化されたアクタークリティック法（TD-Regularized Actor-Critic Methods）</news:title>
   <news:publication_date>2026-07-19T22:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713728</loc>
  <lastmod>2026-07-19T22:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ予測子の有限時間最適性（Finite-time optimality of Bayesian predictors）</news:title>
   <news:publication_date>2026-07-19T22:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713726</loc>
  <lastmod>2026-07-19T22:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高性能・エッジ向けGBDT学習の論理アーキテクチャ（Efficient logic architecture in training gradient boosting decision tree for high-performance and edge computing）</news:title>
   <news:publication_date>2026-07-19T22:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713724</loc>
  <lastmod>2026-07-19T22:30:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシングにおける多源・多時系列データ融合（Multisource and Multitemporal Data Fusion in Remote Sensing）</news:title>
   <news:publication_date>2026-07-19T22:30:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713722</loc>
  <lastmod>2026-07-19T22:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルにおける高速近似測地線（Fast Approximate Geodesics for Deep Generative Models）</news:title>
   <news:publication_date>2026-07-19T22:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713720</loc>
  <lastmod>2026-07-19T22:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的磁性体を用いたアナログ信号処理（Analog Signal Processing Using Stochastic Magnets）</news:title>
   <news:publication_date>2026-07-19T22:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713718</loc>
  <lastmod>2026-07-19T22:30:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>kテスト可能言語の合併学習（Learning Unions of k-Testable Languages）</news:title>
   <news:publication_date>2026-07-19T22:30:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713716</loc>
  <lastmod>2026-07-19T21:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークの幾何学的特徴の統計学習（Statistical learning of geometric characteristics of wireless networks）</news:title>
   <news:publication_date>2026-07-19T21:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713714</loc>
  <lastmod>2026-07-19T21:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的フィードバックを扱うためのファクタリゼーションマシン改良（Factorization Machines for Datasets with Implicit Feedback）</news:title>
   <news:publication_date>2026-07-19T21:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713712</loc>
  <lastmod>2026-07-19T21:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動分類器を科学的計測器として扱う危険性（Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth）</news:title>
   <news:publication_date>2026-07-19T21:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713710</loc>
  <lastmod>2026-07-19T21:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>D3D: 動画の行動認識を軽くする蒸留済み3Dネットワーク（Distilled 3D Networks for Video Action Recognition）</news:title>
   <news:publication_date>2026-07-19T21:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713708</loc>
  <lastmod>2026-07-19T21:36:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不変性・因果性・頑健性が描く予測の新地平（Invariance, Causality and Robustness）</news:title>
   <news:publication_date>2026-07-19T21:36:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713706</loc>
  <lastmod>2026-07-19T21:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核子のパリティ双対性と中性子星構造の新しい見方（Chiral symmetry restoration by parity doubling and the structure of neutron stars）</news:title>
   <news:publication_date>2026-07-19T21:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713704</loc>
  <lastmod>2026-07-19T21:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模序数回帰の新手法（A Novel Large-Scale Ordinal Regression Model）</news:title>
   <news:publication_date>2026-07-19T21:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713702</loc>
  <lastmod>2026-07-19T20:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントカメラの教師なし学習で光学フロー・深度・自動運動を同時に学ぶ（Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotion）</news:title>
   <news:publication_date>2026-07-19T20:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713700</loc>
  <lastmod>2026-07-19T20:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子核内でのハドロン形成を遅い中性子で探る手法（Slow neutron production as a probe of hadron formation in high-energy γ* A reactions）</news:title>
   <news:publication_date>2026-07-19T20:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713698</loc>
  <lastmod>2026-07-19T20:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コストWiFiによる交通モニタリングシステム（DeepWiTraffic: Low Cost WiFi-Based Traffic Monitoring System Using Deep Learning）</news:title>
   <news:publication_date>2026-07-19T20:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713696</loc>
  <lastmod>2026-07-19T20:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークにおける自動学習フレームワークの提案（Toward Intelligent Network Optimization in Wireless Networking: An Auto-learning Framework）</news:title>
   <news:publication_date>2026-07-19T20:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713694</loc>
  <lastmod>2026-07-19T20:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RankGAN: 顔生成における最大マージンランキング型GANの段階的強化（RankGAN: A Maximum Margin Ranking GAN for Generating Faces）</news:title>
   <news:publication_date>2026-07-19T20:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713692</loc>
  <lastmod>2026-07-19T20:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤特定モデルのベイズ的パラメータ推定（Bayesian parameter estimation of miss-specified models）</news:title>
   <news:publication_date>2026-07-19T20:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713690</loc>
  <lastmod>2026-07-19T20:34:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙のガスで読み解く星の成長──PHIBSS2が示した分子ガス主導の銀河進化（PHIBSS2: Molecular Gas and Galaxy Evolution）</news:title>
   <news:publication_date>2026-07-19T20:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713688</loc>
  <lastmod>2026-07-19T19:43:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非教師あり深層学習の医用画像解析への旅路（A Tour of Unsupervised Deep Learning for Medical Image Analysis）</news:title>
   <news:publication_date>2026-07-19T19:43:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713686</loc>
  <lastmod>2026-07-19T19:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒッグス粒子のCP状態判別に向けた機械学習分類（Machine learning classification: case of Higgs boson CP state in H →ττ decay at LHC）</news:title>
   <news:publication_date>2026-07-19T19:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713684</loc>
  <lastmod>2026-07-19T19:42:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力散乱と放射の赤外特性を問う — エイコナル近似による整理（Infrared features of gravitational scattering and radiation in the eikonal approach）</news:title>
   <news:publication_date>2026-07-19T19:42:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713682</loc>
  <lastmod>2026-07-19T19:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム性低減による圧縮センシングの刷新（Derandomizing compressed sensing with combinatorial design）</news:title>
   <news:publication_date>2026-07-19T19:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713680</loc>
  <lastmod>2026-07-19T19:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性と特異性を高める画像キャプショニング（Improving Image Captioning Diversity and Specificity with Specificity-Guided Training）</news:title>
   <news:publication_date>2026-07-19T19:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713678</loc>
  <lastmod>2026-07-19T19:41:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adamが生む暗黙の重みスパース化（Adam Induces Implicit Weight Sparsity in Rectifier Neural Networks）</news:title>
   <news:publication_date>2026-07-19T19:41:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713676</loc>
  <lastmod>2026-07-19T19:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に低消費電力なニューラルTime-of-Flight技術（Very Power Efficient Neural Time-of-Flight）</news:title>
   <news:publication_date>2026-07-19T19:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713674</loc>
  <lastmod>2026-07-19T18:49:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MoDL-MUSSELSによる多ショット回折MRIの位相誤差補正（MoDL-MUSSELS: Model-Based Deep Learning for Multishot Sensitivity-Encoded Diffusion MRI）</news:title>
   <news:publication_date>2026-07-19T18:49:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713672</loc>
  <lastmod>2026-07-19T18:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レプトン–ハドロン散乱に基づく基礎科学の戦略（The “DIS and Related Subjects” Strategy Document: Fundamental Science from Lepton-Hadron Scattering）</news:title>
   <news:publication_date>2026-07-19T18:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713670</loc>
  <lastmod>2026-07-19T18:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周辺分布に基づく新しい距離計量の提案（Chain Rule Optimal Transport）</news:title>
   <news:publication_date>2026-07-19T18:49:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713668</loc>
  <lastmod>2026-07-19T18:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WEKAのRandom Forestを不均衡データ向けに改良する試み（The Random Forest Classifier in WEKA: Discussion and New Developments for Imbalanced Data）</news:title>
   <news:publication_date>2026-07-19T18:48:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713666</loc>
  <lastmod>2026-07-19T18:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープニューラルネットワークのマルウェア耐性強化（Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples）</news:title>
   <news:publication_date>2026-07-19T18:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713664</loc>
  <lastmod>2026-07-19T18:47:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク回避型二段階モデルにおける強凸性の意義（Strong Convexity for Risk-Averse Two-Stage Models with Fixed Complete Linear Recourse）</news:title>
   <news:publication_date>2026-07-19T18:47:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713662</loc>
  <lastmod>2026-07-19T18:47:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数クラスにおけるサンプリング離散化誤差の論点整理（Sampling discretization error for function classes）</news:title>
   <news:publication_date>2026-07-19T18:47:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713660</loc>
  <lastmod>2026-07-19T17:56:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観光領域におけるソーシャルメディア分析が意思決定を変える（Enhancing Decision Making Capacity in Tourism Domain Using Social Media Analytics）</news:title>
   <news:publication_date>2026-07-19T17:56:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713658</loc>
  <lastmod>2026-07-19T17:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エアリアル画像の窓検出とファサード解析（Window detection in aerial texture images of the 3D CityGML Berlin Model）</news:title>
   <news:publication_date>2026-07-19T17:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713656</loc>
  <lastmod>2026-07-19T17:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅層の手がかりを導入した混合モデルによる深層視覚追跡（Shallow Cue Guided Deep Visual Tracking via Mixed Models）</news:title>
   <news:publication_date>2026-07-19T17:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713654</loc>
  <lastmod>2026-07-19T17:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルネット上のサイバーブルイング検出に関する再現性研究（Cyberbullying Detection in Social Networks Using Deep Learning Based Models; A Reproducibility Study）</news:title>
   <news:publication_date>2026-07-19T17:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713652</loc>
  <lastmod>2026-07-19T17:55:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波画像におけるビームフォーミングの学習化（Learning beamforming in ultrasound imaging）</news:title>
   <news:publication_date>2026-07-19T17:55:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713650</loc>
  <lastmod>2026-07-19T17:54:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵画の作家・様式・ジャンルを同時に分類する深層マルチブランチネットワーク（Multitask Painting Categorization by Deep Multibranch Neural Network）</news:title>
   <news:publication_date>2026-07-19T17:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713648</loc>
  <lastmod>2026-07-19T17:54:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レプトン・ジェット相関を用いた核内トモグラフィーの新展開（Lepton-jet Correlations in Deep Inelastic Scattering at the Electron-Ion Collider）</news:title>
   <news:publication_date>2026-07-19T17:54:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713646</loc>
  <lastmod>2026-07-19T17:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>収入データの信頼性評価と階層相関再構築（Credibility evaluation of income data with hierarchical correlation reconstruction）</news:title>
   <news:publication_date>2026-07-19T17:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713644</loc>
  <lastmod>2026-07-19T17:02:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Switch-LSTMsによる多基準中国語形態素解析（Switch-LSTMs for Multi-Criteria Chinese Word Segmentation）</news:title>
   <news:publication_date>2026-07-19T17:02:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713642</loc>
  <lastmod>2026-07-19T17:02:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログレッシブデータサイエンスの可能性と課題 (Progressive Data Science: Potential and Challenges)</news:title>
   <news:publication_date>2026-07-19T17:02:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713640</loc>
  <lastmod>2026-07-19T17:02:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>8ビット浮動小数点で深層学習を学習する意義（Training Deep Neural Networks with 8-bit Floating Point Numbers）</news:title>
   <news:publication_date>2026-07-19T17:02:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713638</loc>
  <lastmod>2026-07-19T17:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能プログラミングにおける「レイジー（怠惰）学習」の実態（On Lazy Training in Differentiable Programming）</news:title>
   <news:publication_date>2026-07-19T17:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713636</loc>
  <lastmod>2026-07-19T17:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子の深いレーザー冷却と効率的磁気圧縮（Deep laser cooling and efficient magnetic compression of molecules）</news:title>
   <news:publication_date>2026-07-19T17:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713634</loc>
  <lastmod>2026-07-19T17:01:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおける自動アカウントの語彙解析（Lexical Analysis of Automated Accounts on Twitter）</news:title>
   <news:publication_date>2026-07-19T17:01:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713632</loc>
  <lastmod>2026-07-19T16:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンコーダを備えた生成モデルの実証研究（An Empirical Study of Generative Models with Encoders）</news:title>
   <news:publication_date>2026-07-19T16:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713630</loc>
  <lastmod>2026-07-19T16:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PnP-AdaNetによるクロスモダリティ医用画像適応（PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation）</news:title>
   <news:publication_date>2026-07-19T16:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713628</loc>
  <lastmod>2026-07-19T16:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケッチ版SVDとレバレッジスコア順序付けの実証的評価（An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering）</news:title>
   <news:publication_date>2026-07-19T16:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713626</loc>
  <lastmod>2026-07-19T16:09:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速適応しきい値による均一ニューラルネットワーク量子化（FAT: Fast Adjustable Threshold for Uniform Neural Network Quantization）</news:title>
   <news:publication_date>2026-07-19T16:09:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713624</loc>
  <lastmod>2026-07-19T16:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AnFlo: Androidアプリにおける機密情報の異常フロー検出（AnFlo: Detecting Anomalous Sensitive Information Flows in Android Apps）</news:title>
   <news:publication_date>2026-07-19T16:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713622</loc>
  <lastmod>2026-07-19T16:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な選好学習：大余白オンライン特徴・ルール学習のゲーム理論的枠組み（Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learning）</news:title>
   <news:publication_date>2026-07-19T16:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713620</loc>
  <lastmod>2026-07-19T16:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層雑音耐性顔復元のための逐次ゲーティングアンサンブルネットワーク（Sequential Gating Ensemble Network for Noise Robust Multi-Scale Face Restoration）</news:title>
   <news:publication_date>2026-07-19T16:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713618</loc>
  <lastmod>2026-07-19T15:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期走行に強い単眼視覚自己位置推定の統合手法（Deep Global-Relative Networks for End-to-End 6-DoF Visual Localization and Odometry）</news:title>
   <news:publication_date>2026-07-19T15:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713616</loc>
  <lastmod>2026-07-19T15:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバーセキュリティにおける機械学習の課題とデータセット（Machine Learning in Cyber-Security - Problems, Challenges and Data Sets）</news:title>
   <news:publication_date>2026-07-19T15:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713614</loc>
  <lastmod>2026-07-19T15:17:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔画像から身長や体型を推定する研究の要点（Physical Attribute Prediction Using Deep Residual Neural Networks）</news:title>
   <news:publication_date>2026-07-19T15:17:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713612</loc>
  <lastmod>2026-07-19T15:17:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク欠測メカニズム下の行列補完（Matrix Completion under Low-Rank Missing Mechanism）</news:title>
   <news:publication_date>2026-07-19T15:17:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713610</loc>
  <lastmod>2026-07-19T15:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域内位置検証のための機械学習（Machine Learning For In-Region Location Verification In Wireless Networks）</news:title>
   <news:publication_date>2026-07-19T15:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713608</loc>
  <lastmod>2026-07-19T15:16:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データスワッピング法による高速かつ高精度な3D医用画像セグメンテーション（Fast and Accurate 3D Medical Image Segmentation with Data-swapping Method）</news:title>
   <news:publication_date>2026-07-19T15:16:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713606</loc>
  <lastmod>2026-07-19T15:16:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜画像の異常検出における半教師あり深層学習（Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images）</news:title>
   <news:publication_date>2026-07-19T15:16:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713604</loc>
  <lastmod>2026-07-19T14:25:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モダリティ間の循環翻訳による頑健な結合表現学習（Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities）</news:title>
   <news:publication_date>2026-07-19T14:25:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713602</loc>
  <lastmod>2026-07-19T14:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミングログからの高速ボットネット検出（Fast Botnet Detection From Streaming Logs Using Online Lanczos Method）</news:title>
   <news:publication_date>2026-07-19T14:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713600</loc>
  <lastmod>2026-07-19T14:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い遷移を導入した翻訳アーキテクチャ（DTMT: A Novel Deep Transition Architecture for Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-19T14:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713598</loc>
  <lastmod>2026-07-19T14:23:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視と熱像のドローン監視を両立する深層学習手法（Towards Visible and Thermal Drone Monitoring with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-19T14:23:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713596</loc>
  <lastmod>2026-07-19T14:23:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ストリーミングデータからの相関異常検出の新展開（Correlated Anomaly Detection from Large Streaming Data）</news:title>
   <news:publication_date>2026-07-19T14:23:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713594</loc>
  <lastmod>2026-07-19T14:23:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽象グラフネットワークとモジュラーメタラーニングによる組合せ一般化（Modular meta-learning in abstract graph networks for combinatorial generalization）</news:title>
   <news:publication_date>2026-07-19T14:23:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713592</loc>
  <lastmod>2026-07-19T14:23:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レビュー評価におけるトピック・感情・嗜好の統合的回帰モデル（Unifying Topic, Sentiment &amp;amp; Preference in an HDP-Based Rating Regression Model for Online Reviews）</news:title>
   <news:publication_date>2026-07-19T14:23:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713590</loc>
  <lastmod>2026-07-19T13:31:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>糖尿病患者の証候弁別のためのCNNベース多インスタンス多タスク学習（CNN based Multi-Instance Multi-Task Learning for Syndrome Differentiation of Diabetic Patients）</news:title>
   <news:publication_date>2026-07-19T13:31:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713588</loc>
  <lastmod>2026-07-19T13:31:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Orchestrate: ハイパーパラメータ最適化における並列実行基盤の設計（Orchestrate: Infrastructure for Enabling Parallelism during Hyperparameter Optimization）</news:title>
   <news:publication_date>2026-07-19T13:31:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713586</loc>
  <lastmod>2026-07-19T13:31:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助タスクを用いた自動運転の視覚制御学習（Learning On-Road Visual Control for Self-Driving Vehicles with Auxiliary Tasks）</news:title>
   <news:publication_date>2026-07-19T13:31:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713584</loc>
  <lastmod>2026-07-19T13:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左右対称性を利用した顔補完の深層CNN（Learning Symmetry Consistent Deep CNNs for Face Completion）</news:title>
   <news:publication_date>2026-07-19T13:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713582</loc>
  <lastmod>2026-07-19T13:30:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽嗜好の十年の変化を検出する新しい特徴抽出手法（Detecting the Trend in Musical Taste over the Decade – A Novel Feature Extraction Algorithm to Classify Musical Content with Simple Features）</news:title>
   <news:publication_date>2026-07-19T13:30:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713580</loc>
  <lastmod>2026-07-19T13:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的ワンショット学習が変える自動運転の視覚認識（Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision）</news:title>
   <news:publication_date>2026-07-19T13:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713578</loc>
  <lastmod>2026-07-19T13:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大多様性分散学習（Max-Diversity Distributed Learning: Theory and Algorithms）</news:title>
   <news:publication_date>2026-07-19T13:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713576</loc>
  <lastmod>2026-07-19T12:38:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病的音声の機械的診断：MFCCとSVMによる実用的アプローチ（Pathological Voice Classification Using Mel-Cepstrum Vectors and Support Vector Machine）</news:title>
   <news:publication_date>2026-07-19T12:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713574</loc>
  <lastmod>2026-07-19T12:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>橋梁損傷検出における単一段検出器と現場点検画像の応用（Bridge Damage Detection using a Single-Stage Detector and Field Inspection Images）</news:title>
   <news:publication_date>2026-07-19T12:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713572</loc>
  <lastmod>2026-07-19T12:38:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆性の破れがランジュバン力学を加速する（Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization）</news:title>
   <news:publication_date>2026-07-19T12:38:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713570</loc>
  <lastmod>2026-07-19T12:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子鍵配送における最適パラメータ予測の機械学習（Machine Learning for Optimal Parameter Prediction in Quantum Key Distribution）</news:title>
   <news:publication_date>2026-07-19T12:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713568</loc>
  <lastmod>2026-07-19T12:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMとAttentionによる金融時系列予測の比較（A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series）</news:title>
   <news:publication_date>2026-07-19T12:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713566</loc>
  <lastmod>2026-07-19T12:37:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>芸術的構図属性を用いたCycleGAN生成制御（Training on Art Composition Attributes to Inﬂuence CycleGAN Art Generation）</news:title>
   <news:publication_date>2026-07-19T12:37:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713564</loc>
  <lastmod>2026-07-19T12:37:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期アライメントのための能動学習とCSI取得（Active Learning and CSI Acquisition for mmWave Initial Alignment）</news:title>
   <news:publication_date>2026-07-19T12:37:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713562</loc>
  <lastmod>2026-07-19T11:46:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テストセットで学習しているのか？（Training on the test set? An analysis of Spampinato et al.）</news:title>
   <news:publication_date>2026-07-19T11:46:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713560</loc>
  <lastmod>2026-07-19T11:46:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナーム和の根単位根での漸近展開が示すもの（Asymptotics of Nahm sums at roots of unity）</news:title>
   <news:publication_date>2026-07-19T11:46:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713558</loc>
  <lastmod>2026-07-19T11:46:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>期待ハイパーボリューム改善の高速かつ厳密な計算（Fast Exact Computation of Expected HyperVolume Improvement）</news:title>
   <news:publication_date>2026-07-19T11:46:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713556</loc>
  <lastmod>2026-07-19T11:45:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習によるオンライン継続適応（DEEP ONLINE LEARNING VIA META-LEARNING: CONTINUAL ADAPTATION FOR MODEL-BASED RL）</news:title>
   <news:publication_date>2026-07-19T11:45:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713554</loc>
  <lastmod>2026-07-19T11:45:16Z</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ポテンシャルを用いた分子動力学（Molecular Dynamics with Neural-Network Potentials）</news:title>
   <news:publication_date>2026-07-19T11:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713552</loc>
  <lastmod>2026-07-19T11:45:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GRUと畳み込みのハイブリッドによる時系列分類の改良（Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classification）</news:title>
   <news:publication_date>2026-07-19T11:45:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713550</loc>
  <lastmod>2026-07-19T11:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算コストの高い数理モデルのエミュレータを効率的に学習する能動学習（Active learning for efficiently training emulators of computationally expensive mathematical models）</news:title>
   <news:publication_date>2026-07-19T11:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713548</loc>
  <lastmod>2026-07-19T10:53:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長時間スケールの分子動力学に対する機械学習の応用（Machine Learning for Molecular Dynamics on Long Timescales）</news:title>
   <news:publication_date>2026-07-19T10:53:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713546</loc>
  <lastmod>2026-07-19T10:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆における軌道予測と集団検出のためのGD-GAN（GD-GAN: Generative Adversarial Networks for Trajectory Prediction and Group Detection in Crowds）</news:title>
   <news:publication_date>2026-07-19T10:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713544</loc>
  <lastmod>2026-07-19T10:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数UAVの軌道設計と出力制御（Trajectory Design and Power Control for Multi-UAV Assisted Wireless Networks: A Machine Learning Approach）</news:title>
   <news:publication_date>2026-07-19T10:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713542</loc>
  <lastmod>2026-07-19T10:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNA接触予測のためのダイレクトカップリング解析の精度評価（Assessing the accuracy of direct-coupling analysis for RNA contact prediction）</news:title>
   <news:publication_date>2026-07-19T10:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713540</loc>
  <lastmod>2026-07-19T10:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>十分な次元削減を深層可変分布で実現する（Deep Variational Sufficient Dimensionality Reduction）</news:title>
   <news:publication_date>2026-07-19T10:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713538</loc>
  <lastmod>2026-07-19T10:52:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ検出とPageRankに基づくファジィ推薦（A Fuzzy Community-Based Recommender System Using PageRank）</news:title>
   <news:publication_date>2026-07-19T10:52:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713536</loc>
  <lastmod>2026-07-19T10:52:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ解像度スキーママッピングシステムの実証（Demonstration of a Multiresolution Schema Mapping System）</news:title>
   <news:publication_date>2026-07-19T10:52:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713534</loc>
  <lastmod>2026-07-19T10:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ指向表現学習（Clustering-Oriented Representation Learning with Attractive-Repulsive Loss）</news:title>
   <news:publication_date>2026-07-19T10:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713532</loc>
  <lastmod>2026-07-19T10:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>束縛プロトンの構造を探る：深部仮想コンプトン散乱による3次元イメージング（Exploring the Structure of the Bound Proton with Deeply Virtual Compton Scattering）</news:title>
   <news:publication_date>2026-07-19T10:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713530</loc>
  <lastmod>2026-07-19T10:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的後続特徴量近似器（Universal Successor Features Approximators）</news:title>
   <news:publication_date>2026-07-19T10:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713528</loc>
  <lastmod>2026-07-19T10:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静的マルウェア分類のためのディープ転移学習（Deep Transfer Learning for Static Malware Classification）</news:title>
   <news:publication_date>2026-07-19T10:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713526</loc>
  <lastmod>2026-07-19T10:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話型推薦の深層化：REDIALデータセットと対話推薦の基礎 (Towards Deep Conversational Recommendations)</news:title>
   <news:publication_date>2026-07-19T10:00:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713524</loc>
  <lastmod>2026-07-19T10:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>wav2letter++：最速のオープンソース音声認識フレームワーク（Wav2Letter++: The Fastest Open-Source Speech Recognition System）</news:title>
   <news:publication_date>2026-07-19T10:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713522</loc>
  <lastmod>2026-07-19T09:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepLensによる視覚データ管理の基盤化（DeepLens: Towards a Visual Data Management System）</news:title>
   <news:publication_date>2026-07-19T09:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713520</loc>
  <lastmod>2026-07-19T09:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画から学ぶ顔モデル（FML: Face Model Learning from Videos）</news:title>
   <news:publication_date>2026-07-19T09:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713518</loc>
  <lastmod>2026-07-19T09:08:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的手法によるニューラルネットワークの堅牢性保証（PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach）</news:title>
   <news:publication_date>2026-07-19T09:08:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713516</loc>
  <lastmod>2026-07-19T09:07:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同符号Wボソン散乱における縦偏極分率の測定と深層学習（Polarization fraction measurement in same-sign WW scattering using deep learning）</news:title>
   <news:publication_date>2026-07-19T09:07:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713514</loc>
  <lastmod>2026-07-19T09:07:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイムな複数人物2D姿勢推定とPart Affinity Fields（OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields）</news:title>
   <news:publication_date>2026-07-19T09:07:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713512</loc>
  <lastmod>2026-07-19T09:07:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HPC向けニューラルネットワークによる近似手法の予備的検討 (A Preliminary Study of Neural Network-based Approximation for HPC Applications)</news:title>
   <news:publication_date>2026-07-19T09:07:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713510</loc>
  <lastmod>2026-07-19T09:07:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Hyper Suprime-Cam 画像と強制測光カタログによる W-CDF-S 光学深度拡張（Deep Hyper Suprime-Cam Images and a Forced Photometry Catalog in W-CDF-S）</news:title>
   <news:publication_date>2026-07-19T09:07:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713508</loc>
  <lastmod>2026-07-19T09:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマホとウェアラブルから行動特徴を抽出する枠組み（Extraction of Behavioral Features from Smartphone and Wearable Data）</news:title>
   <news:publication_date>2026-07-19T09:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713506</loc>
  <lastmod>2026-07-19T08:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報指向探索を用いた深層強化学習の効率化（INFORMATION-DIRECTED EXPLORATION FOR DEEP REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-07-19T08:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713504</loc>
  <lastmod>2026-07-19T08:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XORp：多クラスで絡み合う分類問題のベンチマーク化（XORp: A maximally intertwined p-classes problem）</news:title>
   <news:publication_date>2026-07-19T08:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713502</loc>
  <lastmod>2026-07-19T08:14:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆向き光子＋ジェット生成における横運動量依存フレームワーク（A transverse momentum dependent framework for back-to-back photon+jet production）</news:title>
   <news:publication_date>2026-07-19T08:14:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713500</loc>
  <lastmod>2026-07-19T08:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般多クラス分類に対する一貫したロバスト敵対的予測（Consistent Robust Adversarial Prediction for General Multiclass Classification）</news:title>
   <news:publication_date>2026-07-19T08:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713498</loc>
  <lastmod>2026-07-19T08:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSMツリーに基づくストレージ技術の総覧（LSM-based Storage Techniques: A Survey）</news:title>
   <news:publication_date>2026-07-19T08:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713496</loc>
  <lastmod>2026-07-19T08:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身体動作から捉える反省的思考の自動検出（Automatic Detection of Reflective Thinking in Mathematical Problem Solving based on Unconstrained Bodily Exploration）</news:title>
   <news:publication_date>2026-07-19T08:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713494</loc>
  <lastmod>2026-07-19T08:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像理解のための直接最適化学習（Learning Direct Optimization for Scene Understanding）</news:title>
   <news:publication_date>2026-07-19T08:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713492</loc>
  <lastmod>2026-07-19T07:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピー制約付き学習によるニューラルネットワーク圧縮（Entropy-Constrained Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-19T07:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713490</loc>
  <lastmod>2026-07-19T07:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復注釈でニューラルネットの学習負担を減らす手法（Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis）</news:title>
   <news:publication_date>2026-07-19T07:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713488</loc>
  <lastmod>2026-07-19T07:21:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関ノイズ下での経験的ベイズ正規平均問題の解法（Solving the Empirical Bayes Normal Means Problem with Correlated Noise）</news:title>
   <news:publication_date>2026-07-19T07:21:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713486</loc>
  <lastmod>2026-07-19T07:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的生成モデルによる微分同相（diffeomorphic）登録の学習（Learning a Probabilistic Model for Diffeomorphic Registration）</news:title>
   <news:publication_date>2026-07-19T07:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713484</loc>
  <lastmod>2026-07-19T07:20:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似近傍探索におけるハイパーパラメータの効率的自動調整（Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search）</news:title>
   <news:publication_date>2026-07-19T07:20:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713482</loc>
  <lastmod>2026-07-19T07:20:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的進化的フェデレーテッドラーニング（Multi-objective Evolutionary Federated Learning）</news:title>
   <news:publication_date>2026-07-19T07:20:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713480</loc>
  <lastmod>2026-07-19T07:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要素分解的混合事前分布による構成的深層生成モデル（A Factorial Mixture Prior for Compositional Deep Generative Models）</news:title>
   <news:publication_date>2026-07-19T07:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713478</loc>
  <lastmod>2026-07-19T06:28:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動要約の理論と実務的意義（Automatic Summarization of Natural Language Literature Review and Synthesis）</news:title>
   <news:publication_date>2026-07-19T06:28:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713476</loc>
  <lastmod>2026-07-19T06:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指背画像を用いた偽装検知の実用性と示唆（FDSNet: Finger dorsal image spoof detection network using light field camera）</news:title>
   <news:publication_date>2026-07-19T06:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713474</loc>
  <lastmod>2026-07-19T06:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽い安定核とエキゾチック核におけるクラスタリング（Clusters in light stable and exotic nuclei）</news:title>
   <news:publication_date>2026-07-19T06:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713472</loc>
  <lastmod>2026-07-19T06:09:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atariにおける強化学習のドメイン適応（Domain Adaptation for Reinforcement Learning on the Atari）</news:title>
   <news:publication_date>2026-07-19T06:09:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713470</loc>
  <lastmod>2026-07-19T06:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Momenetによる形状分類の新視点（Momenet: Flavor the Moments in Learning to Classify Shapes）</news:title>
   <news:publication_date>2026-07-19T06:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713468</loc>
  <lastmod>2026-07-19T06:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>査読プロセスにおけるコモンズの悲劇を避ける方法（Avoiding a Tragedy of the Commons in the Peer Review Process）</news:title>
   <news:publication_date>2026-07-19T06:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713466</loc>
  <lastmod>2026-07-19T06:08:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分ドメイン適応を扱うTWINs（TWINs: Two Weighted Inconsistency-reduced Networks for Partial Domain Adaptation）</news:title>
   <news:publication_date>2026-07-19T06:08:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713464</loc>
  <lastmod>2026-07-19T05:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴と潜在行動関数に基づく非パラメトリックユーザクラスタリング（Non-parametric clustering over user features and latent behavioral functions with dual-view mixture models）</news:title>
   <news:publication_date>2026-07-19T05:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713462</loc>
  <lastmod>2026-07-19T05:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子計算と脳の形式的接続（Quantum computing and the brain: quantum nets, dessins d’enfants and neural networks）</news:title>
   <news:publication_date>2026-07-19T05:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713460</loc>
  <lastmod>2026-07-19T05:16:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新しい変分オートエンコーダによる生成・分類・序数回帰への応用（A Novel Variational Autoencoder with Applications to Generative Modelling, Classification, and Ordinal Regression）</news:title>
   <news:publication_date>2026-07-19T05:16:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713458</loc>
  <lastmod>2026-07-19T05:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続的マッチベース学習の実践と評価（Continual Match Based Training in Pommerman）</news:title>
   <news:publication_date>2026-07-19T05:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713456</loc>
  <lastmod>2026-07-19T05:16:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>積分観測を伴うガウス過程における二乗指数共分散関数の評価（Evaluating the squared-exponential covariance function in Gaussian processes with integral observations）</news:title>
   <news:publication_date>2026-07-19T05:16:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713454</loc>
  <lastmod>2026-07-19T05:15:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレア予測と特徴量ランキングの統合手法（Flare forecasting and feature ranking using SDO/HMI data）</news:title>
   <news:publication_date>2026-07-19T05:15:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713452</loc>
  <lastmod>2026-07-19T05:15:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見えない光ネットワーク状態のQoT推定に機械学習を使う意義（Machine Learning for QoT Estimation of Unseen Optical Network States）</news:title>
   <news:publication_date>2026-07-19T05:15:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713450</loc>
  <lastmod>2026-07-19T04:24:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Autoencodersにおけるスパース性の意味（Sparsity in Variational Autoencoders）</news:title>
   <news:publication_date>2026-07-19T04:24:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713448</loc>
  <lastmod>2026-07-19T04:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シムから実世界へ、さらにシムへ（Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks）</news:title>
   <news:publication_date>2026-07-19T04:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713446</loc>
  <lastmod>2026-07-19T04:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attend, Copy, Parseによる文書からのエンドツーエンド情報抽出（Attend, Copy, Parse: End-to-end information extraction from documents）</news:title>
   <news:publication_date>2026-07-19T04:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713444</loc>
  <lastmod>2026-07-19T04:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な最適停止ポリシーの提案（Interpretable Optimal Stopping）</news:title>
   <news:publication_date>2026-07-19T04:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713442</loc>
  <lastmod>2026-07-19T04:23:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クライアント側の負担を劇的に減らす連合学習の工夫（EXPANDING THE REACH OF FEDERATED LEARNING BY REDUCING CLIENT RESOURCE REQUIREMENTS）</news:title>
   <news:publication_date>2026-07-19T04:23:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713440</loc>
  <lastmod>2026-07-19T04:23:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元入力に対する学習最適化による連続軌道生成（Continuous Trajectory Planning Based on Learning Optimization in High Dimensional Input Space for Serial Manipulators）</news:title>
   <news:publication_date>2026-07-19T04:23:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713438</loc>
  <lastmod>2026-07-19T04:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーキンソン字障害のリハビリに対する音楽的ソニフィケーションの概念的枠組み (Music and musical sonification for the rehabilitation of Parkinsonian dysgraphia: Conceptual framework)</news:title>
   <news:publication_date>2026-07-19T04:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713436</loc>
  <lastmod>2026-07-19T03:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数サンプルで学ぶ無線資源管理最適化（LORM: Learning to Optimize for Resource Management in Wireless Networks with Few Training Samples）</news:title>
   <news:publication_date>2026-07-19T03:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713434</loc>
  <lastmod>2026-07-19T03:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高温下で動作するβ-Ga2O3 MSMソーラーブラインド光検出器の光電流メカニズム（High-Temperature Photocurrent Mechanism of β-Ga2O3 Based MSM Solar-Blind Photodetectors）</news:title>
   <news:publication_date>2026-07-19T03:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713432</loc>
  <lastmod>2026-07-19T03:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Frank-Wolfe 法による m-EXACT-SPARSE 問題の解法（Frank-Wolfe Algorithm for the m-EXACT-SPARSE Problem）</news:title>
   <news:publication_date>2026-07-19T03:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713430</loc>
  <lastmod>2026-07-19T03:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラジオ銀河の形態分類を加速する深層自己符号化器の実装（A MACHINE LEARNING BASED MORPHOLOGICAL CLASSIFICATION OF 14,245 RADIO AGNS SELECTED FROM THE BEST–HECKMAN SAMPLE）</news:title>
   <news:publication_date>2026-07-19T03:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713428</loc>
  <lastmod>2026-07-19T03:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN内部の意味階層を可視化する説明グラフ（Explanatory Graphs for CNNs）</news:title>
   <news:publication_date>2026-07-19T03:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713426</loc>
  <lastmod>2026-07-19T03:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークからの解釈可能なAOG表現の抽出（Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering）</news:title>
   <news:publication_date>2026-07-19T03:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713424</loc>
  <lastmod>2026-07-19T03:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載フォグコンピューティングにおけるハンドオーバ最適化に機械学習を用いる（Using Machine Learning for Handover Optimization in Vehicular Fog Computing）</news:title>
   <news:publication_date>2026-07-19T03:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713422</loc>
  <lastmod>2026-07-19T02:39:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Machine Translationによる修正パッチ生成（Learning to Generate Corrective Patches Using Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-19T02:39:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713420</loc>
  <lastmod>2026-07-19T02:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ情報で画質を立て直す一手（SREdgeNet: Edge Enhanced Single Image Super Resolution using Dense Edge Detection Network and Feature Merge Network）</news:title>
   <news:publication_date>2026-07-19T02:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713418</loc>
  <lastmod>2026-07-19T02:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダルなメタ学習による迅速適応の設計（Toward Multimodal Model-Agnostic Meta-Learning）</news:title>
   <news:publication_date>2026-07-19T02:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713416</loc>
  <lastmod>2026-07-19T02:38:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Group-Attention Single-Shot Detector による肺結節検出の革新（Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images）</news:title>
   <news:publication_date>2026-07-19T02:38:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713414</loc>
  <lastmod>2026-07-19T02:37:54Z</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説明（Explaining Neural Networks Semantically and Quantitatively）</news:title>
   <news:publication_date>2026-07-19T02:37:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713412</loc>
  <lastmod>2026-07-19T02:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速・リアルタイム音声スタイル転送のためのオートエンコーダベースアーキテクチャ（Autoencoder Based Architecture for Fast &amp;amp; Real Time Audio Style Transfer）</news:title>
   <news:publication_date>2026-07-19T02:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713410</loc>
  <lastmod>2026-07-19T02:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コーデック選択における一貫収束境界の意義（Uniform Convergence Bounds for Codec Selection）</news:title>
   <news:publication_date>2026-07-19T02:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713408</loc>
  <lastmod>2026-07-19T01:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系統的セレンディピティ：教師なし機械学習による異常検出の実証（Systematic Serendipity: A Test of Unsupervised Machine Learning as a Method for Anomaly Detection）</news:title>
   <news:publication_date>2026-07-19T01:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713406</loc>
  <lastmod>2026-07-19T01:35:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ局所性を高めるモジュラー手法（MatRox: Modular approach for improving data locality in Hierarchical (Mat)rix App(Rox)imation）</news:title>
   <news:publication_date>2026-07-19T01:35:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713404</loc>
  <lastmod>2026-07-19T01:35:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市内車両軌跡予測のための注意機構付きリカレントニューラルネットワーク（Attention-based Recurrent Neural Network for Urban Vehicle Trajectory Prediction）</news:title>
   <news:publication_date>2026-07-19T01:35:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713402</loc>
  <lastmod>2026-07-19T01:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>故障予測と残存寿命を一つのネットワークで同時に扱う手法（Two Birds with One Network: Unifying Failure Event Prediction and Time-to-failure Modeling）</news:title>
   <news:publication_date>2026-07-19T01:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713400</loc>
  <lastmod>2026-07-19T01:35:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル自己符号化器と疎最適化による異常検知と解釈（Anomaly Detection and Interpretation using Multimodal Autoencoder and Sparse Optimization）</news:title>
   <news:publication_date>2026-07-19T01:35:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713398</loc>
  <lastmod>2026-07-19T01:34:50Z</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可視概念化を人の手で導く手法（Interactive Naming for Explaining Deep Neural Networks: A Formative Study）</news:title>
   <news:publication_date>2026-07-19T01:34:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713396</loc>
  <lastmod>2026-07-19T01:34:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスク認識を取り入れた群衆カウントの新手法（Mask-aware networks for crowd counting）</news:title>
   <news:publication_date>2026-07-19T01:34:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713394</loc>
  <lastmod>2026-07-19T00:43:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からのHDR再構成のためのハイブリッド損失（Hybrid Loss for Learning Single-Image-based HDR Reconstruction）</news:title>
   <news:publication_date>2026-07-19T00:43:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713392</loc>
  <lastmod>2026-07-19T00:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索・推薦・オンライン広告における深層強化学習の概観（Deep Reinforcement Learning for Search, Recommendation, and Online Advertising: A Survey）</news:title>
   <news:publication_date>2026-07-19T00:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713390</loc>
  <lastmod>2026-07-19T00:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BANDNET：RNNによるビートルズ風マルチ楽器MIDI作曲機（BANDNET: A NEURAL NETWORK-BASED, MULTI-INSTRUMENT BEATLES-STYLE MIDI MUSIC COMPOSITION MACHINE）</news:title>
   <news:publication_date>2026-07-19T00:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713388</loc>
  <lastmod>2026-07-19T00:42:57Z</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安全性と信頼性に関するサーベイ（A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability）</news:title>
   <news:publication_date>2026-07-19T00:42:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713386</loc>
  <lastmod>2026-07-19T00:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像とテキストの合成による検索革新（Composing Text and Image for Image Retrieval - An Empirical Odyssey）</news:title>
   <news:publication_date>2026-07-19T00:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713384</loc>
  <lastmod>2026-07-19T00:42:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ行動認識のためのマルチレベル系列GAN（Multi-Level Sequence GAN for Group Activity Recognition）</news:title>
   <news:publication_date>2026-07-19T00:42:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713382</loc>
  <lastmod>2026-07-19T00:42:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管の自動抽出とその意義（Retinal Vessel Segmentation based on Fully Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-19T00:42:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713380</loc>
  <lastmod>2026-07-18T23:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意重みを用いたプライベート言語モデルの連合学習（Learning Private Neural Language Modeling with Attentive Aggregation）</news:title>
   <news:publication_date>2026-07-18T23:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713378</loc>
  <lastmod>2026-07-18T23:51:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デモから制約を学ぶ (Learning Constraints from Demonstrations)</news:title>
   <news:publication_date>2026-07-18T23:51:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713376</loc>
  <lastmod>2026-07-18T23:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCT画像の公開データベースが変える臨床研究とAI開発（OCTID: Optical Coherence Tomography Image Database）</news:title>
   <news:publication_date>2026-07-18T23:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713374</loc>
  <lastmod>2026-07-18T23:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ強化学習によるニューラルアーキテクチャ探索の総覧 (A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search)</news:title>
   <news:publication_date>2026-07-18T23:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713372</loc>
  <lastmod>2026-07-18T23:51:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atariモデルズーによる深層強化学習エージェントの可視化と比較（An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents）</news:title>
   <news:publication_date>2026-07-18T23:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713370</loc>
  <lastmod>2026-07-18T23:50:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジーハッシュの学習化による堅牢なファイル類似度計測（Fuzzy Hashing as Perturbation-Consistent Adversarial Kernel Embedding）</news:title>
   <news:publication_date>2026-07-18T23:50:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713368</loc>
  <lastmod>2026-07-18T23:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性確率木を用いた畳み込みニューラルネットワークによる表情認識（Probabilistic Attribute Tree in Convolutional Neural Networks for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-07-18T23:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713366</loc>
  <lastmod>2026-07-18T22:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学に着想を得た神経ダイナミクスを組み込む深層学習（Deep learning incorporating biologically-inspired neural dynamics）</news:title>
   <news:publication_date>2026-07-18T22:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713364</loc>
  <lastmod>2026-07-18T22:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率制約非線形計画問題の効率的フロンティア近似の確率近似法 (A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs)</news:title>
   <news:publication_date>2026-07-18T22:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713362</loc>
  <lastmod>2026-07-18T22:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広域迅速深度サーベイのための賢く色彩豊かな観測戦略（A Smart and Colorful Cadence for the Wide-Fast Deep Survey）</news:title>
   <news:publication_date>2026-07-18T22:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713360</loc>
  <lastmod>2026-07-18T22:59:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転表現の連続性がニューラルネットワークに与える影響（On the Continuity of Rotation Representations in Neural Networks）</news:title>
   <news:publication_date>2026-07-18T22:59:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713358</loc>
  <lastmod>2026-07-18T22:59:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習における報酬のファジィ制御による手書き数字認識（Fuzzy Reward Control for Reinforcement Learning in Handwritten Digit Recognition）</news:title>
   <news:publication_date>2026-07-18T22:59:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713356</loc>
  <lastmod>2026-07-18T22:59:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルサス的強化学習（Malthusian Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-18T22:59:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713354</loc>
  <lastmod>2026-07-18T22:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽器非依存のダスタガ認識を実現するAzarNet（Instrument-Independent Dastgah Recognition of Iranian Classical Music Using AzarNet）</news:title>
   <news:publication_date>2026-07-18T22:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713352</loc>
  <lastmod>2026-07-18T22:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンバランスなデータにおけるマルチインスタンス学習の有効性（Multi Instance Learning For Unbalanced Data）</news:title>
   <news:publication_date>2026-07-18T22:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713350</loc>
  <lastmod>2026-07-18T22:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペルシア語音素認識の実装と評価（Persian phonemes recognition using PPNet）</news:title>
   <news:publication_date>2026-07-18T22:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713348</loc>
  <lastmod>2026-07-18T22:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-Dスキャンの3Dセマンティックインスタンスセグメンテーション（3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans）</news:title>
   <news:publication_date>2026-07-18T22:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713346</loc>
  <lastmod>2026-07-18T22:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフの位相を学習することで進化するドメイン適応（Domain Adaptation on Graphs by Learning Graph Topologies: Theoretical Analysis and an Algorithm）</news:title>
   <news:publication_date>2026-07-18T22:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713344</loc>
  <lastmod>2026-07-18T22:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>h → c c̄ γ によるチャームクォーク・ユカワ結合の探索（Charm-quark Yukawa Coupling in h → c c̄ γ at LHC）</news:title>
   <news:publication_date>2026-07-18T22:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713342</loc>
  <lastmod>2026-07-18T22:06:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペルシア語母音認識におけるMFCCとANNの応用（Persian Vowel recognition with MFCC and ANN on PCVC speech dataset）</news:title>
   <news:publication_date>2026-07-18T22:06:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713340</loc>
  <lastmod>2026-07-18T22:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙初期における大質量休眠銀河の形成史（Massive Dead Galaxies at z ∼2 with HST Grism Spectroscopy）</news:title>
   <news:publication_date>2026-07-18T22:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713338</loc>
  <lastmod>2026-07-18T21:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺IMRT患者に対する3次元線量予測とビーム構成の頑健学習（Three-Dimensional Dose Prediction for Lung IMRT Patients with Deep Neural Networks: Robust Learning from Heterogeneous Beam Configurations）</news:title>
   <news:publication_date>2026-07-18T21:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713336</loc>
  <lastmod>2026-07-18T21:15:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SparseVMによる臨床用スパース3D画像の高速登録（Fast Learning-based Registration of Sparse 3D Clinical Images）</news:title>
   <news:publication_date>2026-07-18T21:15:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713334</loc>
  <lastmod>2026-07-18T21:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー効率を最大化する無線ネットワークの大域最適電力制御（A Globally Optimal Energy-Efficient Power Control Framework and its Efficient Implementation in Wireless Interference Networks）</news:title>
   <news:publication_date>2026-07-18T21:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713332</loc>
  <lastmod>2026-07-18T21:14:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TOP-GANによる少数データでのラベルフリー癌細胞分類（TOP-GAN: Label-free cancer cell classification using deep learning with a small training set）</news:title>
   <news:publication_date>2026-07-18T21:14:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713330</loc>
  <lastmod>2026-07-18T21:14:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルアンサンブル学習による多次元データ処理の革新（Tensor Ensemble Learning for Multidimensional Data）</news:title>
   <news:publication_date>2026-07-18T21:14:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713328</loc>
  <lastmod>2026-07-18T21:13:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザ結合と負荷分散を深層学習で実現する（User Association and Load Balancing for Massive MIMO through Deep Learning）</news:title>
   <news:publication_date>2026-07-18T21:13:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713326</loc>
  <lastmod>2026-07-18T21:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付ファシーズモデルの頑健なパラメータ化に向けて（Towards a Robust Parameterization for Conditioning Facies Models Using Deep Variational Autoencoders and Ensemble Smoother）</news:title>
   <news:publication_date>2026-07-18T21:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713324</loc>
  <lastmod>2026-07-18T20:22:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改良型Deep Belief Networkによる道路安全解析（An Improved Deep Belief Network Model for Road Safety Analyses）</news:title>
   <news:publication_date>2026-07-18T20:22:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713322</loc>
  <lastmod>2026-07-18T20:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散D-MIMO Wi‑Fiネットワークにおけるスループット最適化を目指すDRL応用（Optimizing Throughput Performance in Distributed MIMO Wi-Fi Networks using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-18T20:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713320</loc>
  <lastmod>2026-07-18T20:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的学習による自然言語理解の改善（Multi-task learning to improve natural language understanding）</news:title>
   <news:publication_date>2026-07-18T20:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713318</loc>
  <lastmod>2026-07-18T20:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGBと深度の共通表現を学ぶ（Learning Common Representation from RGB and Depth Images）</news:title>
   <news:publication_date>2026-07-18T20:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713316</loc>
  <lastmod>2026-07-18T20:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均化パラメータ化されたベイズ非負二値行列分解の要点（Bayesian Mean-parameterized Nonnegative Binary Matrix Factorization）</news:title>
   <news:publication_date>2026-07-18T20:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713314</loc>
  <lastmod>2026-07-18T20:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆合成アルゴリズムの現代的再構成（Taking a Deeper Look at the Inverse Compositional Algorithm）</news:title>
   <news:publication_date>2026-07-18T20:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713312</loc>
  <lastmod>2026-07-18T20:12:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生の波形から文字を予測する完全畳み込み音声認識（Fully Convolutional Speech Recognition）</news:title>
   <news:publication_date>2026-07-18T20:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713310</loc>
  <lastmod>2026-07-18T19:21:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語の深い潜在変数モデル入門（A Tutorial on Deep Latent Variable Models of Natural Language）</news:title>
   <news:publication_date>2026-07-18T19:21:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713308</loc>
  <lastmod>2026-07-18T19:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済み深層畳み込みニューラルネットワークを用いた冬期路面状態認識（Winter Road Surface Condition Recognition Using a Pre-trained Deep Convolutional Neural Network）</news:title>
   <news:publication_date>2026-07-18T19:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713306</loc>
  <lastmod>2026-07-18T19:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳–コンピュータ間の転移学習と敵対的変分オートエンコーダ（Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders）</news:title>
   <news:publication_date>2026-07-18T19:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713304</loc>
  <lastmod>2026-07-18T19:11:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AlphaGoにおけるベイズ最適化の実務的意義（Bayesian Optimization in AlphaGo）</news:title>
   <news:publication_date>2026-07-18T19:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713302</loc>
  <lastmod>2026-07-18T19:11:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボヤジアン星の光度低下時における高分解能分光観測（High-resolution spectroscopy of Boyajian’s star during optical dimming events）</news:title>
   <news:publication_date>2026-07-18T19:11:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713300</loc>
  <lastmod>2026-07-18T19:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-Dパッチ表現による顔認識（Discriminant Patch Representation for RGB-D Face Recognition Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-18T19:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713298</loc>
  <lastmod>2026-07-18T19:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール顔特徴から漢方処方を生成する畳み込み手法（Convolutional herbal prescription building method from multi-scale facial features）</news:title>
   <news:publication_date>2026-07-18T19:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713296</loc>
  <lastmod>2026-07-18T18:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多粒子干渉で測るヒルベルト空間の距離（Measuring distances in Hilbert space by many-particle interference）</news:title>
   <news:publication_date>2026-07-18T18:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713294</loc>
  <lastmod>2026-07-18T18:19:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対話型ローカル差分プライバシー下における線形モデル学習の実現（Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations）</news:title>
   <news:publication_date>2026-07-18T18:19:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713292</loc>
  <lastmod>2026-07-18T18:19:23Z</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3D音響イベントの検出と局在化（QUATERNION CONVOLUTIONAL NEURAL NETWORKS FOR DETECTION AND LOCALIZATION OF 3D SOUND EVENTS）</news:title>
   <news:publication_date>2026-07-18T18:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713290</loc>
  <lastmod>2026-07-18T18:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テラヘルツ領域におけるフーリエ単一画素イメージング（Fourier single-pixel imaging in the terahertz regime）</news:title>
   <news:publication_date>2026-07-18T18:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713288</loc>
  <lastmod>2026-07-18T18:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Autoencodersが偶然PCA方向を追う理由（Variational Autoencoders Pursue PCA Directions (by Accident))</news:title>
   <news:publication_date>2026-07-18T18:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713286</loc>
  <lastmod>2026-07-18T18:18:49Z</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トレーサビリティ（Traceability of Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-18T18:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713284</loc>
  <lastmod>2026-07-18T18:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像から犯罪マップを作る試み（Crime Mapping from Satellite Imagery via Deep Learning）</news:title>
   <news:publication_date>2026-07-18T18:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713282</loc>
  <lastmod>2026-07-18T17:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相転移を定量的に調べるための機械学習の普遍性（Machine Learning as a universal tool for quantitative investigations of phase transitions）</news:title>
   <news:publication_date>2026-07-18T17:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713280</loc>
  <lastmod>2026-07-18T17:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なスパース盲分離のヒューリスティクス（Heuristics for Efficient Sparse Blind Source Separation）</news:title>
   <news:publication_date>2026-07-18T17:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713278</loc>
  <lastmod>2026-07-18T17:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈に惑わされない画像認識の作り方（Not Using the Car to See the Sidewalk – Quantifying and Controlling the Effects of Context in Classification and Segmentation）</news:title>
   <news:publication_date>2026-07-18T17:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713276</loc>
  <lastmod>2026-07-18T17:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ICU患者における敗血症予測とバイタルサインの重要度ランキング（Sepsis Prediction and Vital Signs Ranking in Intensive Care Unit Patients）</news:title>
   <news:publication_date>2026-07-18T17:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713274</loc>
  <lastmod>2026-07-18T17:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン上の女性蔑視検出（Hateminers : Detecting Hate speech against Women）</news:title>
   <news:publication_date>2026-07-18T17:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713272</loc>
  <lastmod>2026-07-18T17:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conditional BERTによる文脈的増強（Conditional BERT Contextual Augmentation）</news:title>
   <news:publication_date>2026-07-18T17:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713270</loc>
  <lastmod>2026-07-18T17:25:17Z</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による適応量子状態トモグラフィ（Adaptive Quantum State Tomography with Neural Networks）</news:title>
   <news:publication_date>2026-07-18T17:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713268</loc>
  <lastmod>2026-07-18T16:34:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線音響センサネットワークの多層エネルギー消費モデル（A multi-layered energy consumption model for smart wireless acoustic sensor networks）</news:title>
   <news:publication_date>2026-07-18T16:34:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713266</loc>
  <lastmod>2026-07-18T16:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ下での頑健なグラフ学習（Robust Graph Learning from Noisy Data）</news:title>
   <news:publication_date>2026-07-18T16:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713264</loc>
  <lastmod>2026-07-18T16:23:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BachPropによる音楽生成学習（Learning to Generate Music with BachProp）</news:title>
   <news:publication_date>2026-07-18T16:23:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713262</loc>
  <lastmod>2026-07-18T16:22:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な行列補完：離散最適化によるアプローチ（Interpretable Matrix Completion: A Discrete Optimization Approach）</news:title>
   <news:publication_date>2026-07-18T16:22:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713260</loc>
  <lastmod>2026-07-18T16:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率分布のプライバシー保護型分散推定（Privacy-Preserving Distributed Parameter Estimation for Probability Distribution of Wind Power Forecast Error）</news:title>
   <news:publication_date>2026-07-18T16:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713258</loc>
  <lastmod>2026-07-18T16:22:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定なセーフ・スクリーニングと構造化辞書による高速ℓ1正則化（Stable safe screening and structured dictionaries for faster ℓ1 regularization）</news:title>
   <news:publication_date>2026-07-18T16:22:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713256</loc>
  <lastmod>2026-07-18T16:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間情報を組み入れたグラフ表現学習の開拓（Representation Learning for Spatial Graphs）</news:title>
   <news:publication_date>2026-07-18T16:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713254</loc>
  <lastmod>2026-07-18T15:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な特徴工学による敵対的耐性分類器の設計（Designing Adversarially Resilient Classiﬁers using Resilient Feature Engineering）</news:title>
   <news:publication_date>2026-07-18T15:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713252</loc>
  <lastmod>2026-07-18T15:30:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習によるmp-MRIデータ合成とStitchLayerの提案（Semi-supervised mp-MRI Data Synthesis with StitchLayer and Auxiliary Distance Maximization）</news:title>
   <news:publication_date>2026-07-18T15:30:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713250</loc>
  <lastmod>2026-07-18T15:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ストレージ価格に基づく適応キャッシングの強化学習（Reinforcement Learning for Adaptive Caching with Dynamic Storage Pricing）</news:title>
   <news:publication_date>2026-07-18T15:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713248</loc>
  <lastmod>2026-07-18T15:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習学生ネットワークの特徴埋め込みによる効率化（Learning Student Networks via Feature Embedding）</news:title>
   <news:publication_date>2026-07-18T15:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713246</loc>
  <lastmod>2026-07-18T15:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な売買執行のためのダブルディープQラーニング（Double Deep Q-Learning for Optimal Execution）</news:title>
   <news:publication_date>2026-07-18T15:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713244</loc>
  <lastmod>2026-07-18T15:29:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種データを統合するレコメンダーの深化（Deep Heterogeneous Autoencoders for Collaborative Filtering）</news:title>
   <news:publication_date>2026-07-18T15:29:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713242</loc>
  <lastmod>2026-07-18T15:28:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーキンソン病患者の声紋認識による早期検出（Voiceprint recognition of Parkinson patients based on deep learning）</news:title>
   <news:publication_date>2026-07-18T15:28:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713240</loc>
  <lastmod>2026-07-18T14:37:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製造業向け汎用エンドツーエンド診断フレームワーク（A General End-to-end Diagnosis Framework for Manufacturing Systems）</news:title>
   <news:publication_date>2026-07-18T14:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713238</loc>
  <lastmod>2026-07-18T14:37:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声-視覚コヒーレンスに基づく任意話者のトーキングフェイス生成（Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning）</news:title>
   <news:publication_date>2026-07-18T14:37:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713236</loc>
  <lastmod>2026-07-18T14:37:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク・スパース部分空間クラスタリングにおける非凸正則化の展開（GMC and S0/ℓ0 Regularization for LRSSC）</news:title>
   <news:publication_date>2026-07-18T14:37:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713234</loc>
  <lastmod>2026-07-18T14:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在ディリクレ配分を組み込んだGANによる多峰性画像生成（Latent Dirichlet Allocation in Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-18T14:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713232</loc>
  <lastmod>2026-07-18T14:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学的に妥当なスパイキングニューラルネットワークの教師あり学習法（A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rule）</news:title>
   <news:publication_date>2026-07-18T14:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713230</loc>
  <lastmod>2026-07-18T14:35:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による段階的トリプレットマージンで人物再識別を強化する（Learning Incremental Triplet Margin for Person Re-identification）</news:title>
   <news:publication_date>2026-07-18T14:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713228</loc>
  <lastmod>2026-07-18T14:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子密度から学習して全エネルギーと力を補正する方法（Learning from the Density to Correct Total Energy and Forces in First Principle Simulations）</news:title>
   <news:publication_date>2026-07-18T14:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713226</loc>
  <lastmod>2026-07-18T13:45:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Defense-VAEによる高速で高精度な敵対的攻撃防御（Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks）</news:title>
   <news:publication_date>2026-07-18T13:45:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713224</loc>
  <lastmod>2026-07-18T13:44:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型マルチユーザーモバイルエッジコンピューティングにおける深層強化学習によるオフロード戦略（Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-07-18T13:44:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713222</loc>
  <lastmod>2026-07-18T13:44:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動てんかん発作検出に対する頑健な深層学習アプローチ（A Robust Deep Learning Approach for Automatic Classification of Seizures Against Non-seizures）</news:title>
   <news:publication_date>2026-07-18T13:44:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713220</loc>
  <lastmod>2026-07-18T13:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダ混合に基づく深層クラスタリング（Deep Clustering based on a Mixture of Autoencoders）</news:title>
   <news:publication_date>2026-07-18T13:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713218</loc>
  <lastmod>2026-07-18T13:43:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGBビデオのみで高精度な行動認識を目指す方法（Towards Robust Human Activity Recognition from RGB Video Stream with Limited Labeled Data）</news:title>
   <news:publication_date>2026-07-18T13:43:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713216</loc>
  <lastmod>2026-07-18T13:43:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強烈なミュオンビームで迫る新物理の兆候（Charged Lepton Flavour Violation using Intense Muon Beams at Future Facilities）</news:title>
   <news:publication_date>2026-07-18T13:43:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713214</loc>
  <lastmod>2026-07-18T13:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>福祉実験評価で因果機械学習が付加する価値（What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?）</news:title>
   <news:publication_date>2026-07-18T13:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713212</loc>
  <lastmod>2026-07-18T12:51:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NEOWISEデータの信頼性問題と応答（Response to Wright et al. 2018: Even More Serious Problems with NEOWISE）</news:title>
   <news:publication_date>2026-07-18T12:51:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713210</loc>
  <lastmod>2026-07-18T12:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次モチーフを取り込むスペクトラルクラスタリングの理論（Higher-Order Spectral Clustering under Superimposed Stochastic Block Models）</news:title>
   <news:publication_date>2026-07-18T12:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713208</loc>
  <lastmod>2026-07-18T12:51:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非侵襲的皮膚温度推定法と皮膚感受性指数による深層学習アプローチ（Non-invasive measuring method of skin temperature based on skin sensitivity index and deep learning）</news:title>
   <news:publication_date>2026-07-18T12:51:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713206</loc>
  <lastmod>2026-07-18T12:50:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加重誤分類損失下でのアンサンブル分類（Classification using Ensemble Learning under Weighted Misclassification Loss）</news:title>
   <news:publication_date>2026-07-18T12:50:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713204</loc>
  <lastmod>2026-07-18T12:50:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深く広いニューラルネットワークにおける局所最小の非引力領域（Non-attracting Regions of Local Minima in Deep and Wide Neural Networks）</news:title>
   <news:publication_date>2026-07-18T12:50:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713202</loc>
  <lastmod>2026-07-18T12:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接方策最適化に対する対数バリア法（A Logarithmic Barrier Method For Proximal Policy Optimization）</news:title>
   <news:publication_date>2026-07-18T12:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713200</loc>
  <lastmod>2026-07-18T12:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コード重複が機械学習に及ぼす悪影響（The Adverse Effects of Code Duplication in Machine Learning Models of Code）</news:title>
   <news:publication_date>2026-07-18T12:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713198</loc>
  <lastmod>2026-07-18T11:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動の多忠実度融合とガウス過程の接続（Linking Gaussian Process regression with data-driven manifold embeddings for nonlinear data fusion）</news:title>
   <news:publication_date>2026-07-18T11:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713196</loc>
  <lastmod>2026-07-18T11:58:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デジタルニューロン：組込み向け畳み込みDNN推論アクセラレータ（Digital Neuron: A Hardware Inference Accelerator for Convolutional Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-18T11:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713194</loc>
  <lastmod>2026-07-18T11:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>炭素空孔の受容体準位と捕獲機構の解明（Acceptor levels of the carbon vacancy in 4H-SiC: combining Laplace deep level transient spectroscopy with density functional modeling）</news:title>
   <news:publication_date>2026-07-18T11:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713192</loc>
  <lastmod>2026-07-18T11:57:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドとエッジの協調推論のための自動チューニングニューラルネットワーク量子化フレームワーク (Auto-Tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge)</news:title>
   <news:publication_date>2026-07-18T11:57:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713190</loc>
  <lastmod>2026-07-18T11:57:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係の個数制約を埋め込む方法（Embedding Cardinality Constraints in Neural Link Predictors）</news:title>
   <news:publication_date>2026-07-18T11:57:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713188</loc>
  <lastmod>2026-07-18T11:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Use Case Pointに基づくソフトウェア生産性予測のアンサンブル手法（Ensemble of Learning Project Productivity in Software Effort Based on Use Case Points）</news:title>
   <news:publication_date>2026-07-18T11:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713186</loc>
  <lastmod>2026-07-18T11:56:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>いつ・どこで？マイクロブログストリームによる行動優勢地点予測（When and Where?: Behavior Dominant Location Forecasting with Micro-blog Streams）</news:title>
   <news:publication_date>2026-07-18T11:56:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713184</loc>
  <lastmod>2026-07-18T11:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロショット学習の分類器と典型例の合成（Classifier and Exemplar Synthesis for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-07-18T11:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713182</loc>
  <lastmod>2026-07-18T11:05:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観と動きの深層統合によるモデルフリートラッキング（Model-free Tracking with Deep Appearance and Motion Features Integration）</news:title>
   <news:publication_date>2026-07-18T11:05:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713180</loc>
  <lastmod>2026-07-18T11:04:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚や対話を使わないビジュアル対話の示唆（Visual Dialogue without Vision or Dialogue）</news:title>
   <news:publication_date>2026-07-18T11:04:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713178</loc>
  <lastmod>2026-07-18T11:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローン映像から人物の姿勢と軌跡を推定する手法（Human Pose and Path Estimation from Aerial Video using Dynamic Classifier Selection）</news:title>
   <news:publication_date>2026-07-18T11:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713176</loc>
  <lastmod>2026-07-18T11:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NSCachingによる知識グラフ埋め込みの効率的負例サンプリング（NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding）</news:title>
   <news:publication_date>2026-07-18T11:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713174</loc>
  <lastmod>2026-07-18T11:04:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散特徴に基づく協調学習フレームワーク（FDML: A Collaborative Machine Learning Framework for Distributed Features）</news:title>
   <news:publication_date>2026-07-18T11:04:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713172</loc>
  <lastmod>2026-07-18T11:03:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を手がかりに問いを立てる（Uncertainty as a Guide to Asking Goal-oriented Questions）</news:title>
   <news:publication_date>2026-07-18T11:03:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713170</loc>
  <lastmod>2026-07-18T10:13:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方策分布に基づく情報獲得の探索者（Gold Seeker: Information Gain from Policy Distributions for Goal-oriented Vision-and-Language Reasoning）</news:title>
   <news:publication_date>2026-07-18T10:13:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713168</loc>
  <lastmod>2026-07-18T10:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトラルクラスタリングを最大マージンとレベルセットに結びつける研究（Connecting Spectral Clustering to Maximum Margins and Level Sets）</news:title>
   <news:publication_date>2026-07-18T10:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713166</loc>
  <lastmod>2026-07-18T10:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPCRのバイオアクティブリガンドの自動発見（Automated discovery of GPCR bioactive ligands）</news:title>
   <news:publication_date>2026-07-18T10:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713164</loc>
  <lastmod>2026-07-18T10:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速MVAE: 混合音源の同時分離と分類（FAST MVAE: JOINT SEPARATION AND CLASSIFICATION OF MIXED SOURCES BASED ON MULTICHANNEL VARIATIONAL AUTOENCODER WITH AUXILIARY CLASSIFIER）</news:title>
   <news:publication_date>2026-07-18T10:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713162</loc>
  <lastmod>2026-07-18T10:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済みCNN特徴を用いた表情認識の実務的示唆（Pre-Trained Convolutional Neural Network Features for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-07-18T10:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713160</loc>
  <lastmod>2026-07-18T10:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アップリンクからダウンリンクへのチャネル知識転送（Deep UL2DL: Data-Driven Channel Knowledge Transfer from Uplink to Downlink）</news:title>
   <news:publication_date>2026-07-18T10:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713158</loc>
  <lastmod>2026-07-18T10:11:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量シフト下でのPAC学習保証（PAC Learning Guarantees Under Covariate Shift）</news:title>
   <news:publication_date>2026-07-18T10:11:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713156</loc>
  <lastmod>2026-07-18T09:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分進化フレームワークにおけるPush and Pull探索の組み込み（Embedding Push and Pull Search in the Framework of Differential Evolution for Solving Constrained Single-objective Optimization Problems）</news:title>
   <news:publication_date>2026-07-18T09:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713154</loc>
  <lastmod>2026-07-18T09:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト効果転送のためのTET-GAN（TET-GAN: Text Effects Transfer via Stylization and Destylization）</news:title>
   <news:publication_date>2026-07-18T09:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713152</loc>
  <lastmod>2026-07-18T09:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値化ニューラルネットワークによる効率的な超解像（Efficient Super Resolution Using Binarized Neural Network）</news:title>
   <news:publication_date>2026-07-18T09:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713150</loc>
  <lastmod>2026-07-18T09:19:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階ナレッジ活用共役勾配による到来方向推定（Direction Finding Based on Multi-Step Knowledge-Aided Iterative Conjugate Gradient Algorithms）</news:title>
   <news:publication_date>2026-07-18T09:19:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713148</loc>
  <lastmod>2026-07-18T09:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼領域に基づく敵対的攻撃の効率化（Trust Region Based Adversarial Attack on Neural Networks）</news:title>
   <news:publication_date>2026-07-18T09:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713146</loc>
  <lastmod>2026-07-18T09:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoT向けリソース可変CNN自動合成（Resource-Scalable CNN Synthesis for IoT Applications）</news:title>
   <news:publication_date>2026-07-18T09:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713144</loc>
  <lastmod>2026-07-18T09:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Distill-NetによるIoT向けCNN蒸留（Distill-Net: Application-Specific Distillation of Deep Convolutional Neural Networks for Resource-Constrained IoT Platforms）</news:title>
   <news:publication_date>2026-07-18T09:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713142</loc>
  <lastmod>2026-07-18T08:27:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数動作にまたがる行動品質評価（Action Quality Assessment Across Multiple Actions）</news:title>
   <news:publication_date>2026-07-18T08:27:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713140</loc>
  <lastmod>2026-07-18T08:27:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の証明可能な限界（Provable Limitations of Deep Learning）</news:title>
   <news:publication_date>2026-07-18T08:27:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713138</loc>
  <lastmod>2026-07-18T08:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体上の幾何学的スキャッタリング（Geometric Scattering on Manifolds）</news:title>
   <news:publication_date>2026-07-18T08:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713136</loc>
  <lastmod>2026-07-18T08:26:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動解析による敵対的事例生成の統一的枠組み（Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples）</news:title>
   <news:publication_date>2026-07-18T08:26:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713134</loc>
  <lastmod>2026-07-18T08:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InverSynthによるシンセパラメータ推定の自動化（InverSynth: Deep Estimation of Synthesizer Parameter Configurations from Audio Signals）</news:title>
   <news:publication_date>2026-07-18T08:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713132</loc>
  <lastmod>2026-07-18T08:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意の最適な動的配分（Optimal Dynamic Allocation of Attention）</news:title>
   <news:publication_date>2026-07-18T08:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713130</loc>
  <lastmod>2026-07-18T08:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大内積検索にバンディット戦略（A Bandit Approach to Maximum Inner Product Search）</news:title>
   <news:publication_date>2026-07-18T08:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713128</loc>
  <lastmod>2026-07-18T07:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ効率の高い自動チューニング（Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study）</news:title>
   <news:publication_date>2026-07-18T07:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713126</loc>
  <lastmod>2026-07-18T07:34:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的推定で協調学習を安定化する手法（Likelihood Quantile Networks for Coordinating Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-18T07:34:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713124</loc>
  <lastmod>2026-07-18T07:34:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル単位の文脈注意による顕著領域検出（PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detection）</news:title>
   <news:publication_date>2026-07-18T07:34:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713122</loc>
  <lastmod>2026-07-18T07:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーザープラズマ物理における理論検証と実験条件同定への機械学習の応用 (Employing machine learning for theory validation and identification of experimental conditions in laser-plasma physics)</news:title>
   <news:publication_date>2026-07-18T07:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713120</loc>
  <lastmod>2026-07-18T07:33:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元の代理モデリングと教師付き次元削減（Extending classical surrogate modelling to high dimensions through supervised dimensionality reduction: a data-driven approach）</news:title>
   <news:publication_date>2026-07-18T07:33:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713118</loc>
  <lastmod>2026-07-18T07:33:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リハビリ動作の生成と分類にGANを使う意義（Generative Adversarial Networks for Generation and Classification of Physical Rehabilitation Movement Episodes）</news:title>
   <news:publication_date>2026-07-18T07:33:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713116</loc>
  <lastmod>2026-07-18T07:32:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数課題を同時に最適化する遺伝的手法の発展（Multi-Tasking Genetic Algorithm for Fuzzy System Optimization）</news:title>
   <news:publication_date>2026-07-18T07:32:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713114</loc>
  <lastmod>2026-07-18T06:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差方策学習（Residual Policy Learning）</news:title>
   <news:publication_date>2026-07-18T06:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713112</loc>
  <lastmod>2026-07-18T06:41:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ʋ-SVR多項式カーネルによる新規ソフトウェアプロジェクトの欠陥密度予測（ʋ-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects）</news:title>
   <news:publication_date>2026-07-18T06:41:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713110</loc>
  <lastmod>2026-07-18T06:40:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いたサイバーセキュリティ応用の短評 (A short review on Applications of Deep learning for Cyber security)</news:title>
   <news:publication_date>2026-07-18T06:40:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713108</loc>
  <lastmod>2026-07-18T06:40:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wikipediaを使って単語と実体を数値化する実務ツールの要点解説（Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia）</news:title>
   <news:publication_date>2026-07-18T06:40:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713106</loc>
  <lastmod>2026-07-18T06:40:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストの残差分散を安定的に推定する方法（Consistent Estimation of Residual Variance with Random Forest Out-Of-Bag Errors）</news:title>
   <news:publication_date>2026-07-18T06:40:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713104</loc>
  <lastmod>2026-07-18T06:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定角度下での高分解能位相トモグラフィの深層学習的再構成（High-Resolution Limited-Angle Phase Tomography of Dense Layered Objects Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-18T06:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713102</loc>
  <lastmod>2026-07-18T06:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掌静脈認証用PVSNetの全体像と経営視点での評価（PVSNet: Palm Vein Authentication Siamese Network Trained using Triplet Loss and Adaptive Hard Mining by Learning Enforced Domain Specific Features）</news:title>
   <news:publication_date>2026-07-18T06:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713100</loc>
  <lastmod>2026-07-18T05:48:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群の変換不変表現を学ぶ3DTI-Net（3DTI-Net: Learn Inner Transform Invariant 3D Geometry Features using Dynamic GCN）</news:title>
   <news:publication_date>2026-07-18T05:48:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713098</loc>
  <lastmod>2026-07-18T05:38:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的離散分布分解によるマッチ密度推定（Hierarchical Discrete Distribution Decomposition for Match Density Estimation）</news:title>
   <news:publication_date>2026-07-18T05:38:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713096</loc>
  <lastmod>2026-07-18T05:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Flatten-T Swishによる活性化関数の再考（Flatten-T Swish: a thresholded ReLU-Swish-like activation function for deep learning）</news:title>
   <news:publication_date>2026-07-18T05:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713094</loc>
  <lastmod>2026-07-18T05:38:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変数常微分方程式アルゴリズムと対数凸密度のサンプリング理論（Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities）</news:title>
   <news:publication_date>2026-07-18T05:38:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713092</loc>
  <lastmod>2026-07-18T05:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン間翻訳によるマルチドメイン推薦の新地平（Domain-to-Domain Translation Model for Recommender System）</news:title>
   <news:publication_date>2026-07-18T05:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713090</loc>
  <lastmod>2026-07-18T05:37:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mapperグラフの比較におけるWasserstein系距離の拡張（Mapper Comparison with Wasserstein Metrics）</news:title>
   <news:publication_date>2026-07-18T05:37:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713088</loc>
  <lastmod>2026-07-18T05:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>均衡化した線形文脈バンディットの設計（Balanced Linear Contextual Bandits）</news:title>
   <news:publication_date>2026-07-18T05:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713086</loc>
  <lastmod>2026-07-18T04:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCAを用いた構造化CNN設計の低労力手法（A Low Effort Approach to Structured CNN Design Using PCA）</news:title>
   <news:publication_date>2026-07-18T04:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713084</loc>
  <lastmod>2026-07-18T04:46:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスペクトル畳み込みニューラルネットワークによる太陽電池表面欠陥検出（Multi-spectral Deep Convolutional Neural Network for Solar Cell Defect Detection）</news:title>
   <news:publication_date>2026-07-18T04:46:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713082</loc>
  <lastmod>2026-07-18T04:46:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ABCによる大規模CADモデルデータセット（ABC: A Big CAD Model Dataset For Geometric Deep Learning）</news:title>
   <news:publication_date>2026-07-18T04:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713080</loc>
  <lastmod>2026-07-18T04:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AKARI NEP領域におけるAGNのX線・赤外線関係と高遮蔽降着の探索（X-ray - Infrared relation of AGNs and search for highly obscured accretion in the AKARI NEP Field）</news:title>
   <news:publication_date>2026-07-18T04:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713078</loc>
  <lastmod>2026-07-18T04:45:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Markov等価下での因果同定（Causal Identification under Markov Equivalence）</news:title>
   <news:publication_date>2026-07-18T04:45:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713076</loc>
  <lastmod>2026-07-18T04:45:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復学習手順への差分プライバシー導入の一般的手法（A General Approach to Adding Differential Privacy to Iterative Training Procedures）</news:title>
   <news:publication_date>2026-07-18T04:45:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713074</loc>
  <lastmod>2026-07-18T04:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列集約ネットワークによる密ラベル行動認識の革新（TAN: Temporal Aggregation Network for Dense Multi-label Action Recognition）</news:title>
   <news:publication_date>2026-07-18T04:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713072</loc>
  <lastmod>2026-07-18T03:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学的文脈と生化学イベントの文間関係抽出（Inter-sentence Relation Extraction for Associating Biological Context with Events in Biomedical Texts）</news:title>
   <news:publication_date>2026-07-18T03:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713070</loc>
  <lastmod>2026-07-18T03:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋内ニュートラルホスト向け共有スペクトラムアクセスの深層強化学習アーキテクチャ（Iris: Deep Reinforcement Learning Driven Shared Spectrum Access Architecture for Indoor Neutral-Host Small Cells）</news:title>
   <news:publication_date>2026-07-18T03:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713068</loc>
  <lastmod>2026-07-18T03:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在部分空間を学習する変分オートエンコーダ（Learning Latent Subspaces in Variational Autoencoders）</news:title>
   <news:publication_date>2026-07-18T03:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713066</loc>
  <lastmod>2026-07-18T03:53:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模バッチ学習の経験的モデル (An Empirical Model of Large-Batch Training)</news:title>
   <news:publication_date>2026-07-18T03:53:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713064</loc>
  <lastmod>2026-07-18T03:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人投資家のリスク予測における深層学習の有効性（Can Deep Learning Predict Risky Retail Investors?）</news:title>
   <news:publication_date>2026-07-18T03:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713062</loc>
  <lastmod>2026-07-18T03:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造と協力ゲーム理論を用いた効率的な深層学習解釈（Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory）</news:title>
   <news:publication_date>2026-07-18T03:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713060</loc>
  <lastmod>2026-07-18T03:53:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星団の消散と近傍のUV明るい過輝星が示すもの（The Dissolution of Clusters: What Can We Learn from Nearby, UV-bright, Overluminous Field Stars?）</news:title>
   <news:publication_date>2026-07-18T03:53:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713058</loc>
  <lastmod>2026-07-18T03:02:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仕様誘導型安全検証法：フィードフォワードニューラルネットワーク向け（Specification-Guided Safety Verification for Feedforward Neural Networks）</news:title>
   <news:publication_date>2026-07-18T03:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713056</loc>
  <lastmod>2026-07-18T03:02:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショットで固有表現を学ぶ手法の実用性（Few-shot classification in Named Entity Recognition Task）</news:title>
   <news:publication_date>2026-07-18T03:02:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713054</loc>
  <lastmod>2026-07-18T03:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアス緩和の後処理手法による個人公平性と集団公平性の両立（BIAS MITIGATION POST-PROCESSING FOR INDIVIDUAL AND GROUP FAIRNESS）</news:title>
   <news:publication_date>2026-07-18T03:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713052</loc>
  <lastmod>2026-07-18T03:01:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からのパラメトリック・トップビュー表現（A Parametric Top-View Representation of Complex Road Scenes）</news:title>
   <news:publication_date>2026-07-18T03:01:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713050</loc>
  <lastmod>2026-07-18T03:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘテロジニアスなネットワークにおける連合最適化（Federated Optimization in Heterogeneous Networks）</news:title>
   <news:publication_date>2026-07-18T03:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713048</loc>
  <lastmod>2026-07-18T03:01:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking（Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking）</news:title>
   <news:publication_date>2026-07-18T03:01:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713046</loc>
  <lastmod>2026-07-18T03:01:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一モダリティの手話認識を高めるマルチモーダルトレーニング（Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal Training）</news:title>
   <news:publication_date>2026-07-18T03:01:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713044</loc>
  <lastmod>2026-07-18T02:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L1495-B218フィラメントにおけるアンモニア分光地図とCCS・HC7N化学が示す三様の星形成様式（AN AMMONIA SPECTRAL MAP OF THE L1495-B218 FILAMENTS IN THE TAURUS MOLECULAR CLOUD: II. CCS &amp;amp; HC7N CHEMISTRY AND THREE MODES OF STAR FORMATION IN THE FILAMENTS）</news:title>
   <news:publication_date>2026-07-18T02:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713042</loc>
  <lastmod>2026-07-18T02:10:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェームズ・ウェッブ望遠鏡深宇宙観測における最初の銀河の痕跡 (Signature of the first galaxies in JWST deep field observations)</news:title>
   <news:publication_date>2026-07-18T02:10:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713040</loc>
  <lastmod>2026-07-18T02:09:46Z</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縮尺モデル都市へ：自動車を用いたトラフィック制御のゼロショット方策転移（Simulation to Scaled City: Zero-Shot Policy Transfer for Traffic Control via Autonomous Vehicles）</news:title>
   <news:publication_date>2026-07-18T02:09:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713038</loc>
  <lastmod>2026-07-18T02:09:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dopamine：深層強化学習のための研究フレームワーク（DOPAMINE: A RESEARCH FRAMEWORK FOR DEEP REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-07-18T02:09:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713036</loc>
  <lastmod>2026-07-18T02:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療名詞認識と正規化を同時に学ぶ多タスク学習の枠組み（A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization）</news:title>
   <news:publication_date>2026-07-18T02:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713034</loc>
  <lastmod>2026-07-18T02:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習と継続学習を和解させる—タスクのオンライン混合による適応（Reconciling meta-learning and continual learning with online mixtures of tasks）</news:title>
   <news:publication_date>2026-07-18T02:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713032</loc>
  <lastmod>2026-07-18T02:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電流型深部非弾性散乱における単一ジェット生成のN3LO計算（Jet production in charged-current deep-inelastic scattering to third order in QCD）</news:title>
   <news:publication_date>2026-07-18T02:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713030</loc>
  <lastmod>2026-07-18T01:17:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意モジュールによる映像音声同期判定の研究（On Attention Modules for Audio-Visual Synchronization）</news:title>
   <news:publication_date>2026-07-18T01:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713028</loc>
  <lastmod>2026-07-18T01:17:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非微分可能関数に対するBoosted DCアルゴリズム（The Boosted DC Algorithm for nonsmooth functions）</news:title>
   <news:publication_date>2026-07-18T01:17:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713026</loc>
  <lastmod>2026-07-18T01:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非因子化変分推論が示した時系列モデルの新地平（Non-Factorised Variational Inference in Dynamical Systems）</news:title>
   <news:publication_date>2026-07-18T01:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713024</loc>
  <lastmod>2026-07-18T01:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおける拡散性のスケーラブルかつプライバシー準拠の予測（Scalable Privacy-Compliant Virality Prediction on Twitter）</news:title>
   <news:publication_date>2026-07-18T01:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713022</loc>
  <lastmod>2026-07-18T01:16:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木を使った離散分布の最小最大推定（Discrete minimax estimation with trees）</news:title>
   <news:publication_date>2026-07-18T01:16:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713020</loc>
  <lastmod>2026-07-18T01:16:09Z</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実験をつなぐ転移学習の実践（Transfer learning to model inertial confinement fusion experiments）</news:title>
   <news:publication_date>2026-07-18T01:16:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713018</loc>
  <lastmod>2026-07-18T01:16:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左心室機能と心筋量の自動定量化（Automatic quantification of the LV function and mass: a deep learning approach for cardiovascular MRI）</news:title>
   <news:publication_date>2026-07-18T01:16:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713015</loc>
  <lastmod>2026-07-18T00:25:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロスレスプーリングを用いた高性能超解像（Advanced Super-Resolution using Lossless Pooling Convolutional Networks）</news:title>
   <news:publication_date>2026-07-18T00:25:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713013</loc>
  <lastmod>2026-07-18T00:24:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軌道データから学ぶ相互作用則の非パラメトリック推定（Nonparametric inference of interaction laws in systems of agents from trajectory data）</news:title>
   <news:publication_date>2026-07-18T00:24:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713011</loc>
  <lastmod>2026-07-18T00:24:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ランダム行列の積と深層ニューラルネットワークの勾配安定性（Products of Many Large Random Matrices and Gradients in Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-18T00:24:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713009</loc>
  <lastmod>2026-07-18T00:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的クラス固有判別解析（Probabilistic Class-Specific Discriminant Analysis）</news:title>
   <news:publication_date>2026-07-18T00:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713007</loc>
  <lastmod>2026-07-18T00:24:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス平均ベクトルに着目したカーネル部分空間の設計（Class Mean Vector Component and Discriminant Analysis）</news:title>
   <news:publication_date>2026-07-18T00:24:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713005</loc>
  <lastmod>2026-07-18T00:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル分割による共有モデルガバナンスの拡張（SCALING SHARED MODEL GOVERNANCE VIA MODEL SPLITTING）</news:title>
   <news:publication_date>2026-07-18T00:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713003</loc>
  <lastmod>2026-07-18T00:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUユニットがしばしば死ぬ理由（Why ReLU Units Sometimes Die: Analysis of Single-Unit Error Backpropagation in Neural Networks）</news:title>
   <news:publication_date>2026-07-18T00:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713001</loc>
  <lastmod>2026-07-17T23:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Distributed Submodular Minimization over Networks: a Greedy Column Generation Approach（Distributed Submodular Minimization over Networks: a Greedy Column Generation Approach）</news:title>
   <news:publication_date>2026-07-17T23:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712999</loc>
  <lastmod>2026-07-17T23:32:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AllgathervのマルチGPU性能評価が示す実務的示唆（An Empirical Evaluation of Allgatherv on Multi-GPU Systems）</news:title>
   <news:publication_date>2026-07-17T23:32:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712997</loc>
  <lastmod>2026-07-17T23:31:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGを用いた予測テキストによる通信システム（EEG-based Communication with a Predictive Text Algorithm）</news:title>
   <news:publication_date>2026-07-17T23:31:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712995</loc>
  <lastmod>2026-07-17T23:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ラベル評価指標の反単調性を利用した多ラベルルール誘導（Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules）</news:title>
   <news:publication_date>2026-07-17T23:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712993</loc>
  <lastmod>2026-07-17T23:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルフリーなエンドツーエンド通信システムの学習（Model-free Training of End-to-end Communication Systems）</news:title>
   <news:publication_date>2026-07-17T23:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712991</loc>
  <lastmod>2026-07-17T23:30:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈符号化変分オートエンコーダによる教師なし異常検知（Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection）</news:title>
   <news:publication_date>2026-07-17T23:30:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712989</loc>
  <lastmod>2026-07-17T23:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離計量学習の入門と実践的意義（A TUTORIAL ON DISTANCE METRIC LEARNING: MATHEMATICAL FOUNDATIONS, ALGORITHMS, EXPERIMENTAL ANALYSIS, PROSPECTS AND CHALLENGES）</news:title>
   <news:publication_date>2026-07-17T23:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712987</loc>
  <lastmod>2026-07-17T22:38:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Plackett-Luceモデルの不確実性測定（Deep Plackett-Luce Model with Uncertainty Measurements）</news:title>
   <news:publication_date>2026-07-17T22:38:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712985</loc>
  <lastmod>2026-07-17T22:38:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CEPCルミノメータにおける深層学習ベースのトラック再構築 (Deep learning based track reconstruction on CEPC luminometer)</news:title>
   <news:publication_date>2026-07-17T22:38:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712983</loc>
  <lastmod>2026-07-17T22:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的ペアを用いた単一チャネル盲信号分離への挑戦（TOWARDS UNSUPERVISED SINGLE-CHANNEL BLIND SOURCE SEPARATION USING ADVERSARIAL PAIR UNMIX-AND-REMIX）</news:title>
   <news:publication_date>2026-07-17T22:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712981</loc>
  <lastmod>2026-07-17T22:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ構造の比較評価（Community Structure: A Comparative Evaluation of Community Detection Methods）</news:title>
   <news:publication_date>2026-07-17T22:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712979</loc>
  <lastmod>2026-07-17T22:36:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間融合GANによる画像合成（Spatial Fusion GAN for Image Synthesis）</news:title>
   <news:publication_date>2026-07-17T22:36:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712977</loc>
  <lastmod>2026-07-17T22:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層ごとの特徴量配分を再考する（Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures）</news:title>
   <news:publication_date>2026-07-17T22:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712975</loc>
  <lastmod>2026-07-17T22:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前方カメラを用いた車両縦制御のエンドツーエンド模倣学習（Imitation Learning for End to End Vehicle Longitudinal Control with Forward Camera）</news:title>
   <news:publication_date>2026-07-17T22:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712973</loc>
  <lastmod>2026-07-17T21:44:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子鼻におけるドリフト補正の識別的部分空間射影法（Anti-drift in electronic nose via dimensionality reduction: a discriminative subspace projection approach）</news:title>
   <news:publication_date>2026-07-17T21:44:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712971</loc>
  <lastmod>2026-07-17T21:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分関数拡張が変える学習と性質検査の地平（Partial Function Extension with Applications to Learning and Property Testing）</news:title>
   <news:publication_date>2026-07-17T21:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712969</loc>
  <lastmod>2026-07-17T21:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドライバー注意監視における深層学習と顔の深度マップの統合（Combining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring）</news:title>
   <news:publication_date>2026-07-17T21:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712967</loc>
  <lastmod>2026-07-17T21:35:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像中の文字認識を反復整形で解く新戦略（ESIR: End-to-end Scene Text Recognition via Iterative Image Rectification）</news:title>
   <news:publication_date>2026-07-17T21:35:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712965</loc>
  <lastmod>2026-07-17T21:34:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学進化モデルによる銀河の恒星集団合成（Stellar population synthesis of galaxies with chemical evolution model）</news:title>
   <news:publication_date>2026-07-17T21:34:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712963</loc>
  <lastmod>2026-07-17T21:34:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師ありモノラル歌声分離（SEMI-SUPERVISED MONAURAL SINGING VOICE SEPARATION WITH A MASKING NETWORK TRAINED ON SYNTHETIC MIXTURES）</news:title>
   <news:publication_date>2026-07-17T21:34:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712961</loc>
  <lastmod>2026-07-17T21:34:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性に対処する新しい損失関数による自動左心房セグメンテーション（Combating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation）</news:title>
   <news:publication_date>2026-07-17T21:34:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712959</loc>
  <lastmod>2026-07-17T20:42:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左心房の高精度セグメンテーションのためのピラミッドネットワークとオンライン困難例抽出（Pyramid Network with Online Hard Example Mining for Accurate Left Atrium Segmentation）</news:title>
   <news:publication_date>2026-07-17T20:42:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712957</loc>
  <lastmod>2026-07-17T20:42:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>満足化戦略による実務的な探索の保証（Guaranteed satisﬁcing and ﬁnite regret: Analysis of a cognitive satisﬁcing value function）</news:title>
   <news:publication_date>2026-07-17T20:42:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712955</loc>
  <lastmod>2026-07-17T20:42:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdaFlow: ドメイン適応型密度推定器（ADAFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation）</news:title>
   <news:publication_date>2026-07-17T20:42:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712953</loc>
  <lastmod>2026-07-17T20:40:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル変異検査による敵対的サンプル検出（Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing）</news:title>
   <news:publication_date>2026-07-17T20:40:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712951</loc>
  <lastmod>2026-07-17T20:40:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PointPillarsによる高速点群エンコーダ（PointPillars: Fast Encoders for Object Detection from Point Clouds）</news:title>
   <news:publication_date>2026-07-17T20:40:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712949</loc>
  <lastmod>2026-07-17T20:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストの確率推定を読み解く（Random Forest Probability Estimation: Making Sense of Random Forest Probabilities: a Kernel Perspective）</news:title>
   <news:publication_date>2026-07-17T20:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712947</loc>
  <lastmod>2026-07-17T20:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオベースの人物再識別における深層能動学習（Deep Active Learning for Video-based Person Re-identification）</news:title>
   <news:publication_date>2026-07-17T20:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712945</loc>
  <lastmod>2026-07-17T19:48:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類するな、翻訳せよ：機械翻訳で解く多層Eコマース商品分類（Don’t Classify, Translate: Multi-Level E-Commerce Product Categorization Via Machine Translation）</news:title>
   <news:publication_date>2026-07-17T19:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712943</loc>
  <lastmod>2026-07-17T19:47:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による弱レンズ質量マップのノイズ除去（Denoising Weak Lensing Mass Maps with Deep Learning）</news:title>
   <news:publication_date>2026-07-17T19:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712941</loc>
  <lastmod>2026-07-17T19:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詳細アクセス軌跡を用いた学習行動解析（Using Detailed Access Trajectories for Learning Behavior Analysis）</news:title>
   <news:publication_date>2026-07-17T19:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712939</loc>
  <lastmod>2026-07-17T19:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト対応機械学習に基づくIoTアナリティクス組込みエージェントモデル（An IoT Analytics Embodied Agent Model based on Context-Aware Machine Learning）</news:title>
   <news:publication_date>2026-07-17T19:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712937</loc>
  <lastmod>2026-07-17T19:46:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復型機械学習のための包括的最適化（HELIX: Holistic Optimization for Accelerating Iterative Machine Learning）</news:title>
   <news:publication_date>2026-07-17T19:46:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712935</loc>
  <lastmod>2026-07-17T19:45:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>科学文献からの情報抽出による手法推薦（Information Extraction from Scientific Literature for Method Recommendation）</news:title>
   <news:publication_date>2026-07-17T19:45:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712933</loc>
  <lastmod>2026-07-17T19:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタックド・デノイジング・オートエンコーダを用いたベンガル数字認識の前処理（On Stacked Denoising Autoencoder based Pre-training of ANN for Isolated Handwritten Bengali Numerals Dataset Recognition）</news:title>
   <news:publication_date>2026-07-17T19:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712931</loc>
  <lastmod>2026-07-17T18:53:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きパラメータ推論の事後投影法（Posterior Projection for Inference in Constrained Spaces）</news:title>
   <news:publication_date>2026-07-17T18:53:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712929</loc>
  <lastmod>2026-07-17T18:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対の一様K安定性（On uniform K-stability of pairs）</news:title>
   <news:publication_date>2026-07-17T18:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712927</loc>
  <lastmod>2026-07-17T18:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的ソフトマックスの有効性（Effectiveness of Hierarchical Softmax in Large Scale Classification Tasks）</news:title>
   <news:publication_date>2026-07-17T18:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712925</loc>
  <lastmod>2026-07-17T18:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トレーニングセットのカモフラージュ（Training Set Camouflage）</news:title>
   <news:publication_date>2026-07-17T18:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712923</loc>
  <lastmod>2026-07-17T18:51:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUネットワークが訓練データから離れた地点で高信頼を出す理由とその緩和方法（Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem）</news:title>
   <news:publication_date>2026-07-17T18:51:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712921</loc>
  <lastmod>2026-07-17T18:51:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフに効く確率的スペクトル埋め込み（Stochastic Gradient Descent for Spectral Embedding with Implicit Orthogonality Constraint）</news:title>
   <news:publication_date>2026-07-17T18:51:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712919</loc>
  <lastmod>2026-07-17T18:51:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の視覚関係の検出（Detecting Unseen Visual Relations Using Analogies）</news:title>
   <news:publication_date>2026-07-17T18:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712917</loc>
  <lastmod>2026-07-17T17:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるスパース化と収束解析（Convergence of a Relaxed Variable Splitting Method for Learning Sparse Neural Networks via ℓ1, ℓ0, and Transformed-ℓ1 Penalties）</news:title>
   <news:publication_date>2026-07-17T17:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712915</loc>
  <lastmod>2026-07-17T17:58:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値ハイパーディメンショナル表現の埋め込み法が変えるMI-BCI（Exploring Embedding Methods in Binary Hyperdimensional Computing: A Case Study for Motor-Imagery based Brain–Computer Interfaces）</news:title>
   <news:publication_date>2026-07-17T17:58:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712913</loc>
  <lastmod>2026-07-17T17:58:30Z</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・インテント・スロットの結合表現学習（COUPLED REPRESENTATION LEARNING FOR DOMAINS, INTENTS AND SLOTS IN SPOKEN LANGUAGE UNDERSTANDING）</news:title>
   <news:publication_date>2026-07-17T17:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712911</loc>
  <lastmod>2026-07-17T17:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分割回帰モデリング (Split Regression Modeling)</news:title>
   <news:publication_date>2026-07-17T17:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712909</loc>
  <lastmod>2026-07-17T17:57:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高スループットがん薬スクリーニングにおける用量反応モデリング（Dose-response modeling in high-throughput cancer drug screenings: An end-to-end approach）</news:title>
   <news:publication_date>2026-07-17T17:57:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712907</loc>
  <lastmod>2026-07-17T17:57:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストコーパスから社会的バイアスを測るための平滑化ファーストオーダー共起法（Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence）</news:title>
   <news:publication_date>2026-07-17T17:57:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712905</loc>
  <lastmod>2026-07-17T17:57:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANとVAEの違いを読み解く検証的プローブ（A Probe Towards Understanding GAN and VAE Models）</news:title>
   <news:publication_date>2026-07-17T17:57:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712903</loc>
  <lastmod>2026-07-17T17:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所銀河群の矮小銀河における星形成履歴の洞察（The star formation histories of dwarf galaxies in Local Group cosmological simulations）</news:title>
   <news:publication_date>2026-07-17T17:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712901</loc>
  <lastmod>2026-07-17T17:05:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルRNNによる系列予測（Sequence Prediction Using Spectral RNNs）</news:title>
   <news:publication_date>2026-07-17T17:05:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712899</loc>
  <lastmod>2026-07-17T17:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIGNet: セマンティックインスタンスを利用した教師なし3D幾何認識（SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception）</news:title>
   <news:publication_date>2026-07-17T17:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712897</loc>
  <lastmod>2026-07-17T17:04:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長編動画を正確に言い当てるための推論改良（Adversarial Inference for Multi-Sentence Video Description）</news:title>
   <news:publication_date>2026-07-17T17:04:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712895</loc>
  <lastmod>2026-07-17T17:04:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Boosted Dark Matterイベント生成モジュールの実装と意義（A Module For Boosted Dark Matter Event Generation in GENIE）</news:title>
   <news:publication_date>2026-07-17T17:04:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712893</loc>
  <lastmod>2026-07-17T17:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結晶対称性のニューラルネットワーク分類（Neural Network-based Classification of Crystal Symmetries from X-Ray Diffraction Patterns）</news:title>
   <news:publication_date>2026-07-17T17:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712891</loc>
  <lastmod>2026-07-17T17:03:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子多フェルミオン輸送を機械学習で探る（Probing transport in quantum many-fermion simulations via quantum loop topography）</news:title>
   <news:publication_date>2026-07-17T17:03:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712889</loc>
  <lastmod>2026-07-17T16:12:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>若いコア崩壊型超新星残骸E0102の詳細解析（A DETAILED ARCHIVAL CHANDRA STUDY OF THE YOUNG CORE-COLLAPSE SUPERNOVA REMNANT 1E 0102.2-7219 IN THE SMALL MAGELLANIC CLOUD）</news:title>
   <news:publication_date>2026-07-17T16:12:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712887</loc>
  <lastmod>2026-07-17T16:12:35Z</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を用いた軟組織の高速生体力学モデリング（Towards Fast Biomechanical Modeling of Soft Tissue Using Neural Networks）</news:title>
   <news:publication_date>2026-07-17T16:12:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712885</loc>
  <lastmod>2026-07-17T16:12:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超新星理論とニュートリノ物理の共進化史（A Brief History of the Co-evolution of Supernova Theory with Neutrino Physics）</news:title>
   <news:publication_date>2026-07-17T16:12:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712883</loc>
  <lastmod>2026-07-17T16:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分方程式の制約を解析的に埋め込む手法（Analytically Embedding Differential Equation Constraints into Least Squares Support Vector Machines using the Theory of Functional Connections）</news:title>
   <news:publication_date>2026-07-17T16:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712881</loc>
  <lastmod>2026-07-17T16:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGBDスキャンからのシーン再構成：Learning-based ICPによる3D CAD配置（Scene Recomposition by Learning-based ICP）</news:title>
   <news:publication_date>2026-07-17T16:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712879</loc>
  <lastmod>2026-07-17T16:11:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称バタフライ速度の実現（Asymmetric butterfly velocities in Hamiltonian and circuit models）</news:title>
   <news:publication_date>2026-07-17T16:11:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712877</loc>
  <lastmod>2026-07-17T16:10:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強い物質—光子相互作用に対する縮約密度行列アプローチ（Reduced Density-Matrix Approach to Strong Matter-Photon Interaction）</news:title>
   <news:publication_date>2026-07-17T16:10:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712875</loc>
  <lastmod>2026-07-17T15:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索意識的強化学習の再検討（Exploration Conscious Reinforcement Learning Revisited）</news:title>
   <news:publication_date>2026-07-17T15:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712873</loc>
  <lastmod>2026-07-17T15:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長い動画における技能評価の順位認識時間的注意（The Pros and Cons: Rank-aware Temporal Attention for Skill Determination in Long Videos）</news:title>
   <news:publication_date>2026-07-17T15:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712871</loc>
  <lastmod>2026-07-17T15:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テトラッドとq理論（Tetrads and q-theory）</news:title>
   <news:publication_date>2026-07-17T15:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/712869</loc>
  <lastmod>2026-07-17T15:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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