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   <news:title>共通ソースグラフを持つデータセットのカノニカル相関分析（Canonical Correlation Analysis of Datasets with a Common Source Graph）</news:title>
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   <news:title>再考：EEGベースの非侵襲的脳インタフェースの設計（Re-thinking EEG-based non-invasive brain interfaces: modeling and analysis）</news:title>
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   <news:title>電子構造計算のための量子機械学習（Quantum Machine Learning for Electronic Structure Calculations）</news:title>
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   <news:title>スペクトルから銀河の物理量を推定する機械学習手法の進化（GAME: GAlaxy Machine learning for Emission lines）</news:title>
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   <news:title>カーネルリッジ回帰におけるクラスタリングと階層行列形式の研究（A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>プライバシー保護された予測（Privacy-preserving Prediction）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>CANDELSにおける多波長バルジ・ディスク分解カタログ（A catalog of polychromatic bulge-disk decompositions of ~17.600 galaxies in CANDELS）</news:title>
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   <news:title>疾患軌跡を読むための深層学習アプローチ（Disease-Atlas: Navigating Disease Trajectories using Deep Learning）</news:title>
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    <news:language>ja</news:language>
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   <news:title>深い優先度衝突のゼロオーバーヘッドな曖昧性除去（Towards Zero-Overhead Disambiguation of Deep Priority Conflicts）</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>個人間の相互作用予測（Predicting interactions between individuals with structural and dynamical information）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-21T00:17:26Z</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>HDM-Netによる単眼非剛体3D再構成の新展開（HDM-Net: Monocular Non-Rigid 3D Reconstruction with Learned Deformation Model）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>単一分子ナノポア検出のための畳み込みニューラルネットワークQuipuNet（QuipuNet: convolutional neural network for single-molecule nanopore sensing）</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>カーネル行列近似のための分散適応サンプリング（Distributed Adaptive Sampling for Kernel Matrix Approximation）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>Stein Pointsによる代表点列による事後近似の効率化（Stein Points）</news:title>
   <news:publication_date>2026-04-21T00:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-21T00:13:51Z</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>周囲カメラとルートプランナーを用いた運転モデルのエンドツーエンド学習 (End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners)</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-21T00:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>逐次拡張による畳み込みニューラルネットワークの学習効率化（Incremental Training of Deep Convolutional Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T23:21:44Z</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>安全なエンドツーエンド模倣学習によるモデル予測制御（Safe end-to-end imitation learning for model predictive control）</news:title>
   <news:publication_date>2026-04-20T23:21:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T23:21:30Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>学習による分岐（Learning to Branch）</news:title>
   <news:publication_date>2026-04-20T23:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T23:21:10Z</lastmod>
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   <news:title>話者適応の実証評価（Empirical Evaluation of Speaker Adaptation on DNN based Acoustic Model）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T23:20:20Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>あなたはメタデータ：ソーシャルメディア利用者の識別と難読化（You Are Your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T23:20:06Z</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>タスク境界を前提としない継続学習の実装（Task Agnostic Continual Learning Using Online Variational Bayes）</news:title>
   <news:publication_date>2026-04-20T23:20:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T23:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>音声の残響除去におけるGANの活用（Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition）</news:title>
   <news:publication_date>2026-04-20T23:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T23:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ベンガル語の実数読み上げ音声コーパスの構築（Comprehending Real Numbers: Development of Bengali Real Number Speech Corpus）</news:title>
   <news:publication_date>2026-04-20T23:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T22:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護型機械学習の脅威と解決策（Privacy Preserving Machine Learning: Threats and Solutions）</news:title>
   <news:publication_date>2026-04-20T22:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T22:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>世界モデルの構築と活用（World Models）</news:title>
   <news:publication_date>2026-04-20T22:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/681622</loc>
  <lastmod>2026-04-20T22:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>長期的形状変化分布の学習：微分同相写像の多様体上の階層モデル（Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms）</news:title>
   <news:publication_date>2026-04-20T22:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T22:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepScores：小さな物体の検出・分類のための大規模楽譜データセット（DeepScores – A Dataset for Segmentation, Detection and Classification of Tiny Objects）</news:title>
   <news:publication_date>2026-04-20T22:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/681618</loc>
  <lastmod>2026-04-20T22:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張演算子による点群畳み込み（Point Convolutional Neural Networks by Extension Operators）</news:title>
   <news:publication_date>2026-04-20T22:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/681616</loc>
  <lastmod>2026-04-20T22:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>CHiME-4を使った雑音下音声認識の単一ベースライン構築（Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T22:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるDNAハイブリダイゼーション解析（Analyzing DNA Hybridization via machine learning）</news:title>
   <news:publication_date>2026-04-20T22:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T21:33:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な多領域ディープニューラルネットワークの表現（Efficient parametrization of multi-domain deep neural networks）</news:title>
   <news:publication_date>2026-04-20T21:33:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/681610</loc>
  <lastmod>2026-04-20T21:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepJDOTによる深層結合分布の最適輸送で実現する教師なしドメイン適応（DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-04-20T21:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681608</loc>
  <lastmod>2026-04-20T21:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク理論と機械学習を用いたエルニーニョ予測（Using network theory and machine learning to predict El Niño）</news:title>
   <news:publication_date>2026-04-20T21:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681606</loc>
  <lastmod>2026-04-20T21:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的PETのキネティック圧縮センシング（Kinetic Compressive Sensing）</news:title>
   <news:publication_date>2026-04-20T21:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681604</loc>
  <lastmod>2026-04-20T21:31:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルグラフ畳み込みニューラルネットワークの要点と経営への示唆（Tensor graph convolutional neural network）</news:title>
   <news:publication_date>2026-04-20T21:31:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681602</loc>
  <lastmod>2026-04-20T21:31:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>6自由度オブジェクトトラッキングの評価フレームワーク (A Framework for Evaluating 6-DOF Object Trackers)</news:title>
   <news:publication_date>2026-04-20T21:31:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681600</loc>
  <lastmod>2026-04-20T21:31:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性メモリによる高速パラメトリック学習（Fast Parametric Learning with Activation Memorization）</news:title>
   <news:publication_date>2026-04-20T21:31:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681598</loc>
  <lastmod>2026-04-20T20:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの深度学習と焦点距離の埋め込み（Learning Depth from Single Images with Deep Neural Network Embedding Focal Length）</news:title>
   <news:publication_date>2026-04-20T20:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681596</loc>
  <lastmod>2026-04-20T20:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Return of the features — 効率的な特徴選択と解釈性の高いフォトメトリック赤方偏移推定（Efficient feature selection and interpretation for photometric redshifts）</news:title>
   <news:publication_date>2026-04-20T20:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681594</loc>
  <lastmod>2026-04-20T20:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンゴテクスチャ画像の高精度分類を目指して（Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation）</news:title>
   <news:publication_date>2026-04-20T20:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681592</loc>
  <lastmod>2026-04-20T20:36:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BLSTMマスクを使った単一チャネル音声強調の学生–教師学習（Student-Teacher Learning for BLSTM Mask-based Speech Enhancement）</news:title>
   <news:publication_date>2026-04-20T20:36:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681590</loc>
  <lastmod>2026-04-20T20:36:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベント時刻だけからネットワーク接続を推定する理論（Inferring network connectivity from event timing patterns）</news:title>
   <news:publication_date>2026-04-20T20:36:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681588</loc>
  <lastmod>2026-04-20T20:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元空間における交差検証の効率化（Cross-validation in high-dimensional spaces: a lifeline for least-squares models and multi-class LDA）</news:title>
   <news:publication_date>2026-04-20T20:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T20:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆に紛れるプライベート平均化の実現（Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries）</news:title>
   <news:publication_date>2026-04-20T20:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681584</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を用いた公平な動的価格設定（Reinforcement Learning for Fair Dynamic Pricing）</news:title>
   <news:publication_date>2026-04-20T19:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681582</loc>
  <lastmod>2026-04-20T19:44:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>押しと掴みの協調を自己監督で学ぶ（Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T19:44:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681580</loc>
  <lastmod>2026-04-20T19:43:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い非弾性散乱におけるジェット生成のN3LO補正（N3LO Corrections to Jet Production in Deep Inelastic Scattering using the Projection-to-Born Method）</news:title>
   <news:publication_date>2026-04-20T19:43:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681578</loc>
  <lastmod>2026-04-20T19:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波検出器における雑音トランジェントの画像ベース深層学習による分類（Image-based deep learning for classification of noise transients in gravitational wave detectors）</news:title>
   <news:publication_date>2026-04-20T19:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681576</loc>
  <lastmod>2026-04-20T19:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮した特徴列のための二重注意マッチングネットワーク (Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification)</news:title>
   <news:publication_date>2026-04-20T19:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681574</loc>
  <lastmod>2026-04-20T19:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素数値Restricted Boltzmann Machineによる複素スペクトルからの直接音声パラメータ化（Complex-Valued Restricted Boltzmann Machine for Direct Speech Parameterization from Complex Spectra）</news:title>
   <news:publication_date>2026-04-20T19:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681572</loc>
  <lastmod>2026-04-20T19:42:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-20T19:42:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681570</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Diagonalwise RefactorizationによるDepthwise Convolutionの高速学習（Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions）</news:title>
   <news:publication_date>2026-04-20T18:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681568</loc>
  <lastmod>2026-04-20T18:50:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>匿名化されたマルチエージェント環境におけるエントロピー基準の独立学習（Entropy Based Independent Learning in Anonymous Multi-Agent Settings）</news:title>
   <news:publication_date>2026-04-20T18:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681566</loc>
  <lastmod>2026-04-20T18:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作り特徴と深層姿勢ベース領域特徴の融合による人物再識別（Person re-identification with fusion of hand-crafted and deep pose-based body region features）</news:title>
   <news:publication_date>2026-04-20T18:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681564</loc>
  <lastmod>2026-04-20T18:50:02Z</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の解剖（Demystifying Differentiable Programming: Shift/Reset the Penultimate Backpropagator）</news:title>
   <news:publication_date>2026-04-20T18:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681562</loc>
  <lastmod>2026-04-20T18:49:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数判別器を用いたCycleGANによる非並列音声ドメイン適応（A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation）</news:title>
   <news:publication_date>2026-04-20T18:49:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681560</loc>
  <lastmod>2026-04-20T18:49:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mittens：既存語彙表現を領域特化させる手法（Mittens: An Extension of GloVe for Learning Domain-Specialized Representations）</news:title>
   <news:publication_date>2026-04-20T18:49:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681558</loc>
  <lastmod>2026-04-20T18:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール構造認識ネットワークによる姿勢推定（Multi-Scale Structure-Aware Network for Human Pose Estimation）</news:title>
   <news:publication_date>2026-04-20T18:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681556</loc>
  <lastmod>2026-04-20T17:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標から逆算して学ぶ強化学習（Forward-Backward Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T17:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681554</loc>
  <lastmod>2026-04-20T17:58:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLE誘導尤度によるマルコフ確率場の近似 (MLE-induced Likelihood for Markov Random Fields)</news:title>
   <news:publication_date>2026-04-20T17:58:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681552</loc>
  <lastmod>2026-04-20T17:57:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CISE分散研究インフラの未来（The Future of CISE Distributed Research Infrastructure）</news:title>
   <news:publication_date>2026-04-20T17:57:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681550</loc>
  <lastmod>2026-04-20T17:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitter API制限を回避するウェブスクレイピング手法（A Web Scraping Methodology for Bypassing Twitter API Restrictions）</news:title>
   <news:publication_date>2026-04-20T17:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681548</loc>
  <lastmod>2026-04-20T17:56:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画ベース人物再識別のための多様性正則化時空間注意（Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification）</news:title>
   <news:publication_date>2026-04-20T17:56:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681546</loc>
  <lastmod>2026-04-20T17:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CompNetによる脳MRIの抽出精度向上（CompNet: Complementary Segmentation Network for Brain MRI Extraction）</news:title>
   <news:publication_date>2026-04-20T17:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681544</loc>
  <lastmod>2026-04-20T17:56:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DRACO：冗長勾配によるビザンチン耐性分散学習（Byzantine-resilient Distributed Training via Redundant Gradients）</news:title>
   <news:publication_date>2026-04-20T17:56:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681542</loc>
  <lastmod>2026-04-20T17:04:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-20T17:04:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T17:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師的サンプルマイニングによる人間機械協調の促進（Towards Human-Machine Cooperation: Self-supervised Sample Mining for Object Detection）</news:title>
   <news:publication_date>2026-04-20T17:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UCT木探索によるエンパワーメント計算の高速化（Accelerating Empowerment Computation with UCT Tree Search）</news:title>
   <news:publication_date>2026-04-20T17:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681536</loc>
  <lastmod>2026-04-20T17:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>てんかん発作検出の深層学習アプローチ（Epileptic Seizure Detection: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-04-20T17:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681534</loc>
  <lastmod>2026-04-20T17:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性を作用素として扱う：未知の属性-物体組合せの分解 (Attributes as Operators: Factorizing Unseen Attribute-Object Compositions)</news:title>
   <news:publication_date>2026-04-20T17:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681532</loc>
  <lastmod>2026-04-20T17:01:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家庭内暴力の再犯予測における決定木アプローチ（A Decision Tree Approach to Predicting Recidivism in Domestic Violence）</news:title>
   <news:publication_date>2026-04-20T17:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681530</loc>
  <lastmod>2026-04-20T17:01:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Webから学ぶセマンティックセグメンテーション（WebSeg: Learning Semantic Segmentation from Web Searches）</news:title>
   <news:publication_date>2026-04-20T17:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681528</loc>
  <lastmod>2026-04-20T16:09:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンクド・オープンデータにおける基礎的区別の実証的分析（Empirical Analysis of Foundational Distinctions in Linked Open Data）</news:title>
   <news:publication_date>2026-04-20T16:09:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681526</loc>
  <lastmod>2026-04-20T16:09:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるメタ安定多形の振動特性予測（Vibrational properties of metastable polymorph structures by machine learning）</news:title>
   <news:publication_date>2026-04-20T16:09:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681524</loc>
  <lastmod>2026-04-20T16:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない注釈データで地表画像をピクセル単位で識別する方法（Low-Shot Learning for the Semantic Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-04-20T16:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681522</loc>
  <lastmod>2026-04-20T16:08:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雪上の女性も写すキャプション生成の偏りを正す研究（Women also Snowboard: Overcoming Bias in Captioning Models）</news:title>
   <news:publication_date>2026-04-20T16:08:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681520</loc>
  <lastmod>2026-04-20T16:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのハイパーパラメータに対する規律あるアプローチ（A Disciplined Approach to Neural Network Hyper-Parameters: Part 1 – Learning Rate, Batch Size, Momentum, and Weight Decay）</news:title>
   <news:publication_date>2026-04-20T16:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681518</loc>
  <lastmod>2026-04-20T16:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声強調における模倣損失の導入（SPECTRAL FEATURE MAPPING WITH MIMIC LOSS FOR ROBUST SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-04-20T16:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681516</loc>
  <lastmod>2026-04-20T16:07:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルデータ解析のための深層学習（Deep learning as a tool for neural data analysis: speech classification and cross-frequency coupling in human sensorimotor cortex）</news:title>
   <news:publication_date>2026-04-20T16:07:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681514</loc>
  <lastmod>2026-04-20T15:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別的プーリングによる動画表現学習 (Video Representation Learning Using Discriminative Pooling)</news:title>
   <news:publication_date>2026-04-20T15:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681512</loc>
  <lastmod>2026-04-20T15:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的環境でゴール指向の自律性を示すチャットボット（On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments）</news:title>
   <news:publication_date>2026-04-20T15:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681510</loc>
  <lastmod>2026-04-20T15:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然勾配とテイラー近似を結ぶ共通枠組み（A Common Framework for Natural Gradient and Taylor based Optimisation using Manifold Theory）</news:title>
   <news:publication_date>2026-04-20T15:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681508</loc>
  <lastmod>2026-04-20T15:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能な属性・識別共同深層学習による教師なし人物再識別（Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification）</news:title>
   <news:publication_date>2026-04-20T15:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681506</loc>
  <lastmod>2026-04-20T15:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膨張黒鉛に埋め込まれたタンタル標的のスケール試作と陽子ビーム衝撃下の評価（Scaled prototype of a tantalum target embedded in expanded graphite for antiproton production）</news:title>
   <news:publication_date>2026-04-20T15:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681504</loc>
  <lastmod>2026-04-20T15:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習アーキテクチャにおける量子もつれの表現力（Quantum Entanglement in Deep Learning Architectures）</news:title>
   <news:publication_date>2026-04-20T15:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681502</loc>
  <lastmod>2026-04-20T15:04:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短時間実行で不良設定を素早く打ち切るための方策学習（Algorithm Configuration: Learning policies for the quick termination of poor performers）</news:title>
   <news:publication_date>2026-04-20T15:04:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681500</loc>
  <lastmod>2026-04-20T14:13:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JWSTに向けた高赤方偏移のUV光度関数予測（Semi-analytic forecasts for JWST - I. UV luminosity functions at z = 4 - 10）</news:title>
   <news:publication_date>2026-04-20T14:13:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681498</loc>
  <lastmod>2026-04-20T14:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換的状態による未来予測（Predicting the Future with Transformational States）</news:title>
   <news:publication_date>2026-04-20T14:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681496</loc>
  <lastmod>2026-04-20T14:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別最適化モデルを分散で学ぶ方法—DJAM（DJAM: distributed Jacobi asynchronous method for learning personal models）</news:title>
   <news:publication_date>2026-04-20T14:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681494</loc>
  <lastmod>2026-04-20T14:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動ロボットによる回復性のある能動的情報収集（Resilient Active Information Gathering with Mobile Robots）</news:title>
   <news:publication_date>2026-04-20T14:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681492</loc>
  <lastmod>2026-04-20T14:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙における暗黒物質–バリオン散乱の制約と21cm信号への示唆（Early‑Universe Constraints on Dark Matter-Baryon Scattering and their Implications for a Global 21cm Signal）</news:title>
   <news:publication_date>2026-04-20T14:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681490</loc>
  <lastmod>2026-04-20T14:11:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン転移に強い属性埋め込みを用いた識別モデル（Domain transfer convolutional attribute embedding）</news:title>
   <news:publication_date>2026-04-20T14:11:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681488</loc>
  <lastmod>2026-04-20T14:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識に特化した軽量GRU設計：Light GRU（Light Gated Recurrent Units for Speech Recognition）</news:title>
   <news:publication_date>2026-04-20T14:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681486</loc>
  <lastmod>2026-04-20T13:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野外での3D人体姿勢推定を敵対的学習で実現する（3D Human Pose Estimation in the Wild by Adversarial Learning）</news:title>
   <news:publication_date>2026-04-20T13:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681484</loc>
  <lastmod>2026-04-20T13:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stereoによる高精度深度推定の重要性と効率的半教師あり学習（On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach）</news:title>
   <news:publication_date>2026-04-20T13:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681482</loc>
  <lastmod>2026-04-20T13:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Polygon-RNN++による効率的なポリゴン注釈（Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++）</news:title>
   <news:publication_date>2026-04-20T13:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681480</loc>
  <lastmod>2026-04-20T13:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列予測における記憶ベースの序数回帰深層ニューラルネットワーク（MOrdReD: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting）</news:title>
   <news:publication_date>2026-04-20T13:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681478</loc>
  <lastmod>2026-04-20T13:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きから読み解くフロー：ウェアラブルと深層学習による最適パフォーマンス検出（Flow From Motion: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-04-20T13:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681476</loc>
  <lastmod>2026-04-20T13:16:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と機械が共に学ぶHAMLET：説明可能なラベリング改善手法（HAMLET: Interpretable Human And Machine co-LEarning Technique）</news:title>
   <news:publication_date>2026-04-20T13:16:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681474</loc>
  <lastmod>2026-04-20T13:16:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ画像と機械学習で先読みする受信電力予測（Proactive Received Power Prediction Using Machine Learning and Depth Images for mmWave Networks）</news:title>
   <news:publication_date>2026-04-20T13:16:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681472</loc>
  <lastmod>2026-04-20T12:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BAGANによる不均衡データのためのデータ拡張（BAGAN: Data Augmentation with Balancing GAN）</news:title>
   <news:publication_date>2026-04-20T12:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681470</loc>
  <lastmod>2026-04-20T12:24:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像表現の内在次元（On the Intrinsic Dimensionality of Image Representations）</news:title>
   <news:publication_date>2026-04-20T12:24:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681468</loc>
  <lastmod>2026-04-20T12:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光の偏光を芸術と結びつけて教える教育実践（Teaching Light Polarization by Putting Art and Physics Together）</news:title>
   <news:publication_date>2026-04-20T12:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681466</loc>
  <lastmod>2026-04-20T12:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数巡回セールスマン問題を学習する順序不変プーリングネットワーク（Learning the Multiple Traveling Salesmen Problem with Permutation Invariant Pooling Networks）</news:title>
   <news:publication_date>2026-04-20T12:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681464</loc>
  <lastmod>2026-04-20T12:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的例の部分空間を特徴づける局所内在次元の限界（ON THE LIMITATION OF LOCAL INTRINSIC DIMENSIONALITY FOR CHARACTERIZING THE SUBSPACES OF ADVERSARIAL EXAMPLES）</news:title>
   <news:publication_date>2026-04-20T12:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681462</loc>
  <lastmod>2026-04-20T12:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体信号の類似性に基づく階層的クラスタリングで健康状態を識別する（Similarity based hierarchical clustering of physiological parameters for the identification of health states – a feasibility study）</news:title>
   <news:publication_date>2026-04-20T12:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681460</loc>
  <lastmod>2026-04-20T12:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的に生成されるペアワイズ制約による距離学習が耳認識にもたらす変化（Metric Learning with Dynamically Generated Pairwise Constraints for Ear Recognition）</news:title>
   <news:publication_date>2026-04-20T12:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681458</loc>
  <lastmod>2026-04-20T11:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像データセットの分類難易度を高速推定する方法（Efficient Image Dataset Classification Difficulty Estimation for Predicting Deep-Learning Accuracy）</news:title>
   <news:publication_date>2026-04-20T11:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681456</loc>
  <lastmod>2026-04-20T11:30:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セッションベース推薦アルゴリズムの評価（Evaluation of Session-based Recommendation Algorithms）</news:title>
   <news:publication_date>2026-04-20T11:30:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681454</loc>
  <lastmod>2026-04-20T11:29:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一スコア比較では機械学習手法の優劣は決められない（Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approaches）</news:title>
   <news:publication_date>2026-04-20T11:29:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681452</loc>
  <lastmod>2026-04-20T11:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム性質予測のための一般的なパスベース表現（A General Path-Based Representation for Predicting Program Properties）</news:title>
   <news:publication_date>2026-04-20T11:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681450</loc>
  <lastmod>2026-04-20T11:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピックとソーシャル潜在因子を組み込んだ協調フィルタリング（Collaborative Filtering with Topic and Social Latent Factors Incorporating Implicit Feedback）</news:title>
   <news:publication_date>2026-04-20T11:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681448</loc>
  <lastmod>2026-04-20T11:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる予測区間を作る方法（Calibrated Prediction Intervals for Neural Network Regressors）</news:title>
   <news:publication_date>2026-04-20T11:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681446</loc>
  <lastmod>2026-04-20T11:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークにおける長期短期記憶と学習の学習（Long short-term memory and learning-to-learn in networks of spiking neurons）</news:title>
   <news:publication_date>2026-04-20T11:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681444</loc>
  <lastmod>2026-04-20T10:35:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マッチングパースートと座標降下の統一的解析（On Matching Pursuit and Coordinate Descent）</news:title>
   <news:publication_date>2026-04-20T10:35:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681442</loc>
  <lastmod>2026-04-20T10:35:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生履修履歴から学ぶ接続主義的レコメンデーション（Connectionist Recommendation in the Wild: On the utility and scrutability of neural networks for personalized course guidance）</news:title>
   <news:publication_date>2026-04-20T10:35:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681440</loc>
  <lastmod>2026-04-20T10:34:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子生成モデルの評価指標としてのFréchet ChemNet Distance（Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery）</news:title>
   <news:publication_date>2026-04-20T10:34:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681438</loc>
  <lastmod>2026-04-20T10:33:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者来院データの深層表現化（Deep Representation for Patient Visits from Electronic Health Records）</news:title>
   <news:publication_date>2026-04-20T10:33:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681436</loc>
  <lastmod>2026-04-20T10:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に対する理論的に正しい訓練アルゴリズムの実装可能性（A Provably Correct Algorithm for Deep Learning that Actually Works）</news:title>
   <news:publication_date>2026-04-20T10:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681434</loc>
  <lastmod>2026-04-20T10:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己注意に基づく音響モデル（Self-Attentional Acoustic Models）</news:title>
   <news:publication_date>2026-04-20T10:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681432</loc>
  <lastmod>2026-04-20T10:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株式のクラスタ分析と高頻度データの活用（Cluster analysis of stocks using price movements of high frequency data from National Stock Exchange）</news:title>
   <news:publication_date>2026-04-20T10:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681430</loc>
  <lastmod>2026-04-20T09:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoT大量機器向けAloha-NOMAによる非同期ランダムアクセスの提案（Enabling Aloha-NOMA for Massive M2M Communication in IoT Networks）</news:title>
   <news:publication_date>2026-04-20T09:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681428</loc>
  <lastmod>2026-04-20T09:41:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インフレーションの決定的な未来（The decisive future of inflation）</news:title>
   <news:publication_date>2026-04-20T09:41:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681426</loc>
  <lastmod>2026-04-20T09:41:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑な活動の無教師分割（Unsupervised Learning and Segmentation of Complex Activities from Video）</news:title>
   <news:publication_date>2026-04-20T09:41:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681424</loc>
  <lastmod>2026-04-20T09:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードをベクトルで表す思想と実践（code2vec: Learning Distributed Representations of Code）</news:title>
   <news:publication_date>2026-04-20T09:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681422</loc>
  <lastmod>2026-04-20T09:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック・シースルー光場レンダリング（Semantic See-Through Rendering on Light Fields）</news:title>
   <news:publication_date>2026-04-20T09:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681420</loc>
  <lastmod>2026-04-20T09:39:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>界面再結合と注入障壁がペロブスカイト太陽電池の電気特性に与える影響（The effects of interfacial recombination and injection barrier on the electrical characteristics of perovskite solar cells）</news:title>
   <news:publication_date>2026-04-20T09:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681418</loc>
  <lastmod>2026-04-20T09:38:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差ランダム効果モデルのスケーラブル推論（Scalable inference for crossed random effects models）</news:title>
   <news:publication_date>2026-04-20T09:38:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681416</loc>
  <lastmod>2026-04-20T08:46:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報蒸留ネットワークによる高速・高精度単一画像超解像（Fast and Accurate Single Image Super-Resolution via Information Distillation Network）</news:title>
   <news:publication_date>2026-04-20T08:46:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681414</loc>
  <lastmod>2026-04-20T08:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサーパターンノイズと深層学習によるCG判別（Distinguishing Computer-generated Graphics from Natural Images Based on Sensor Pattern Noise and Deep Learning）</news:title>
   <news:publication_date>2026-04-20T08:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681412</loc>
  <lastmod>2026-04-20T08:46:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時分割多重化によるスケーラブルな光フォトニック強化学習（Scalable photonic reinforcement learning by time-division multiplexing of laser chaos）</news:title>
   <news:publication_date>2026-04-20T08:46:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681410</loc>
  <lastmod>2026-04-20T08:45:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成敵対ネットワークを用いたマルチサイト脳画像の差異補正（Correcting differences in multi-site neuroimaging data using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-20T08:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681408</loc>
  <lastmod>2026-04-20T08:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律走行における深層学習アーキテクチャの体系的比較（A Systematic Comparison of Deep Learning Architectures in an Autonomous Vehicle）</news:title>
   <news:publication_date>2026-04-20T08:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681406</loc>
  <lastmod>2026-04-20T08:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン二次法による非凸確率的最適化（Online Second Order Methods for Non-Convex Stochastic Optimizations）</news:title>
   <news:publication_date>2026-04-20T08:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681404</loc>
  <lastmod>2026-04-20T08:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答における一般化ハダマード積融合演算子（Generalized Hadamard-Product Fusion Operators for Visual Question Answering）</news:title>
   <news:publication_date>2026-04-20T08:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681402</loc>
  <lastmod>2026-04-20T07:53:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不適切学習が切り拓くオンラインロジスティック回帰の新展開（Logistic Regression: The Importance of Being Improper）</news:title>
   <news:publication_date>2026-04-20T07:53:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681400</loc>
  <lastmod>2026-04-20T07:44:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認証におけるパッチ特徴とソフト顔属性を組み合わせた署名（A Face Recognition Signature Combining Patch-based Features with Soft Facial Attributes）</news:title>
   <news:publication_date>2026-04-20T07:44:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681398</loc>
  <lastmod>2026-04-20T07:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的リスクの局所最小値について（On the Local Minima of the Empirical Risk）</news:title>
   <news:publication_date>2026-04-20T07:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681396</loc>
  <lastmod>2026-04-20T07:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的汚染に強い確率的バンディット（Stochastic bandits robust to adversarial corruptions）</news:title>
   <news:publication_date>2026-04-20T07:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681394</loc>
  <lastmod>2026-04-20T07:43:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態変換と損失変換で見るニューラルネットの構造（Neural Nets via Forward State Transformation and Backward Loss Transformation）</news:title>
   <news:publication_date>2026-04-20T07:43:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681392</loc>
  <lastmod>2026-04-20T07:43:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepVesselNet：3次元血管画像から血管構造を効率的に抽出する手法（DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes）</news:title>
   <news:publication_date>2026-04-20T07:43:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681390</loc>
  <lastmod>2026-04-20T07:42:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRI画像の学習ベース品質管理（Learning-Based Quality Control for Cardiac MR Images）</news:title>
   <news:publication_date>2026-04-20T07:42:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681388</loc>
  <lastmod>2026-04-20T06:51:33Z</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勾配安定化を実現するSVDパラメータ化（Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization）</news:title>
   <news:publication_date>2026-04-20T06:51:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681386</loc>
  <lastmod>2026-04-20T06:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師あり学習としてのテキスト分割（Text Segmentation as a Supervised Learning Task）</news:title>
   <news:publication_date>2026-04-20T06:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681384</loc>
  <lastmod>2026-04-20T06:51:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一RGB-D画像の深度補完（Deep Depth Completion of a Single RGB-D Image）</news:title>
   <news:publication_date>2026-04-20T06:51:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681382</loc>
  <lastmod>2026-04-20T06:50:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仕様のあいまいさを「見える化」するスケルトン合成（Synthesizing Skeletons for Reactive Systems）</news:title>
   <news:publication_date>2026-04-20T06:50:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681380</loc>
  <lastmod>2026-04-20T06:50:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SUNLayerによる安定的な復元：生成ネットワークでのデノイズ理論（SUNLayer: Stable denoising with generative networks）</news:title>
   <news:publication_date>2026-04-20T06:50:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681378</loc>
  <lastmod>2026-04-20T06:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルエッジコンピューティングの性能最適化（Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T06:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681376</loc>
  <lastmod>2026-04-20T06:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型クロージャーの発見（Data-driven Discovery of Closure Models）</news:title>
   <news:publication_date>2026-04-20T06:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681374</loc>
  <lastmod>2026-04-20T05:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群変換の双方向学習ネットワーク（P2P-NET: Bidirectional Point Displacement Net for Shape Transform）</news:title>
   <news:publication_date>2026-04-20T05:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681372</loc>
  <lastmod>2026-04-20T05:58:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さい頭部検出を精緻化する手法の実務的解説（Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture）</news:title>
   <news:publication_date>2026-04-20T05:58:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681370</loc>
  <lastmod>2026-04-20T05:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COSMOS領域におけるDEIMOS 10K分光サーベイカタログ（The DEIMOS 10K Spectroscopic Survey Catalog of the COSMOS Field）</news:title>
   <news:publication_date>2026-04-20T05:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681368</loc>
  <lastmod>2026-04-20T05:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフのベルヌーイ埋め込み（Bernoulli Embeddings for Graphs）</news:title>
   <news:publication_date>2026-04-20T05:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681366</loc>
  <lastmod>2026-04-20T05:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動車のランプ合流を強化学習で行う研究（Autonomous Ramp Merge Maneuver Based on Reinforcement Learning with Continuous Action Space）</news:title>
   <news:publication_date>2026-04-20T05:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681364</loc>
  <lastmod>2026-04-20T05:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Goldbach関数の近似に深層学習を使う（Goldbach’s Function Approximation Using Deep Learning）</news:title>
   <news:publication_date>2026-04-20T05:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681362</loc>
  <lastmod>2026-04-20T05:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習に基づく教師なしドメイン適応（Unsupervised Domain Adaptation: A Multi-task Learning-based Method）</news:title>
   <news:publication_date>2026-04-20T05:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681360</loc>
  <lastmod>2026-04-20T05:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール畳み込みによる環境音認識の前進（Learning Environmental Sounds with Multi-scale Convolutional Neural Network）</news:title>
   <news:publication_date>2026-04-20T05:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681358</loc>
  <lastmod>2026-04-20T05:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの教師なし深度推定と顔の3D回転・置換（Unsupervised Depth Estimation, 3D Face Rotation and Replacement）</news:title>
   <news:publication_date>2026-04-20T05:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681356</loc>
  <lastmod>2026-04-20T05:05:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話環境下での深層強化学習による自動運転操作（Automated Driving Maneuvers under Interactive Environment based on Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T05:05:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681354</loc>
  <lastmod>2026-04-20T05:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク履歴の回復性における相転移（Phase transition in the recoverability of network history）</news:title>
   <news:publication_date>2026-04-20T05:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681352</loc>
  <lastmod>2026-04-20T05:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>服の「相性」を学ぶ──タイプ認識埋め込みによるファッション互換性の新視点（Learning Type-Aware Embeddings for Fashion Compatibility）</news:title>
   <news:publication_date>2026-04-20T05:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681350</loc>
  <lastmod>2026-04-20T05:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知システムの出力フィードバック制御に関する有限データ性能保証（Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System）</news:title>
   <news:publication_date>2026-04-20T05:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681348</loc>
  <lastmod>2026-04-20T05:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーングラフ解析を依存構文解析として扱う手法（Scene Graph Parsing as Dependency Parsing）</news:title>
   <news:publication_date>2026-04-20T05:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681346</loc>
  <lastmod>2026-04-20T04:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから現実世界への教師なしドメイン適応（Unsupervised Domain Adaptation: from Simulation Engine to the Real World）</news:title>
   <news:publication_date>2026-04-20T04:11:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681344</loc>
  <lastmod>2026-04-20T04:11:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な生存データに対するバランス化ランダム生存森林（Balanced Random Survival Forests for Extremely Unbalanced, Right Censored Data）</news:title>
   <news:publication_date>2026-04-20T04:11:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681342</loc>
  <lastmod>2026-04-20T04:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース音声からテキスト翻訳（Low-Resource Speech-to-Text Translation）</news:title>
   <news:publication_date>2026-04-20T04:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681340</loc>
  <lastmod>2026-04-20T04:09:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣耐性プログラム挙動モデリング（Mimicry Resilient Program Behavior Modeling with LSTM based Branch Models）</news:title>
   <news:publication_date>2026-04-20T04:09:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681338</loc>
  <lastmod>2026-04-20T04:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器は“安全舞台”に過ぎない — 探索的攻撃に対する脆弱性の実証（Security Theater: On the Vulnerability of Classifiers to Exploratory Attacks）</news:title>
   <news:publication_date>2026-04-20T04:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681336</loc>
  <lastmod>2026-04-20T04:08:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮画像に「ノイズ」を再導入して自然さを取り戻す技術（Noise generation for compression algorithms）</news:title>
   <news:publication_date>2026-04-20T04:08:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681334</loc>
  <lastmod>2026-04-20T04:08:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的敵対的マイニングによる機械学習の安全性（A Dynamic-Adversarial Mining Approach to the Security of Machine Learning）</news:title>
   <news:publication_date>2026-04-20T04:08:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681332</loc>
  <lastmod>2026-04-20T03:16:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的コンセプトドリフトへの対処法（Handling Adversarial Concept Drift in Streaming Data）</news:title>
   <news:publication_date>2026-04-20T03:16:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681330</loc>
  <lastmod>2026-04-20T03:16:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化実験で影響を受けた集団を効率的に見つける方法（Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection）</news:title>
   <news:publication_date>2026-04-20T03:16:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681328</loc>
  <lastmod>2026-04-20T03:16:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な変分ベイズによる重厚尾PLDAのi-vector/x-vectorへの応用（Fast variational Bayes for heavy-tailed PLDA applied to i-vectors and x-vectors）</news:title>
   <news:publication_date>2026-04-20T03:16:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681326</loc>
  <lastmod>2026-04-20T03:15:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイク・アンド・スラブ深層学習の事後収束（Posterior Concentration for Sparse Deep Learning）</news:title>
   <news:publication_date>2026-04-20T03:15:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681324</loc>
  <lastmod>2026-04-20T03:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非共役変分推論における自然勾配の実践（Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models）</news:title>
   <news:publication_date>2026-04-20T03:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681322</loc>
  <lastmod>2026-04-20T03:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公共図書館におけるソーシャルメディア分析の実務的示唆（Social Media Analysis for Organizations: US Public Libraries）</news:title>
   <news:publication_date>2026-04-20T03:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681320</loc>
  <lastmod>2026-04-20T03:14:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲイユーザーのツイートから見える疾病像の把握（Characterizing Diseases and Disorders In Gay Users’ Tweets）</news:title>
   <news:publication_date>2026-04-20T03:14:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681318</loc>
  <lastmod>2026-04-20T02:23:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別のための多層因子分解ネットワーク（Multi-Level Factorisation Net for Person Re-Identification）</news:title>
   <news:publication_date>2026-04-20T02:23:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681316</loc>
  <lastmod>2026-04-20T02:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エゴセントリック映像における視線予測：タスク依存注意遷移の学習（Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition）</news:title>
   <news:publication_date>2026-04-20T02:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681314</loc>
  <lastmod>2026-04-20T02:22:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペットと幸福度の関係：大規模ソーシャルメディア解析から読み解く示唆（The Effect of Pets on Happiness: A Large-scale Multi-Factor Analysis using Social Multimedia）</news:title>
   <news:publication_date>2026-04-20T02:22:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681312</loc>
  <lastmod>2026-04-20T02:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子もつれに導かれる機械学習アーキテクチャ（Entanglement-guided architectures of machine learning by quantum tensor network）</news:title>
   <news:publication_date>2026-04-20T02:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681310</loc>
  <lastmod>2026-04-20T02:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepWarpによるDNNベースの非線形変形（DeepWarp: DNN-based Nonlinear Deformation）</news:title>
   <news:publication_date>2026-04-20T02:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681308</loc>
  <lastmod>2026-04-20T02:22:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Machine Learning and Applied Linguistics (Machine Learning and Applied Linguistics)</news:title>
   <news:publication_date>2026-04-20T02:22:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681306</loc>
  <lastmod>2026-04-20T02:21:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元最適化を読み解くための単純モデル：ガウスランダム場上の勾配降下法（Gradient descent in Gaussian random fields as a toy model for high-dimensional optimisation in deep learning）</news:title>
   <news:publication_date>2026-04-20T02:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681304</loc>
  <lastmod>2026-04-20T01:30:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像生成と改変のためのGAN技術比較（Comparing Generative Adversarial Network Techniques for Image Creation and Modification）</news:title>
   <news:publication_date>2026-04-20T01:30:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681302</loc>
  <lastmod>2026-04-20T01:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における動きの規則性を教師なしで学ぶ敵対的枠組み（Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos）</news:title>
   <news:publication_date>2026-04-20T01:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681300</loc>
  <lastmod>2026-04-20T01:30:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接ブロック座標降下法による深層ニューラルネットワーク学習（A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training）</news:title>
   <news:publication_date>2026-04-20T01:30:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681298</loc>
  <lastmod>2026-04-20T01:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習データの重み付け学習による頑健な深層学習（Learning to Reweight Examples for Robust Deep Learning）</news:title>
   <news:publication_date>2026-04-20T01:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681296</loc>
  <lastmod>2026-04-20T01:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレンジ推論による機械読解（Multi-range Reasoning for Machine Comprehension）</news:title>
   <news:publication_date>2026-04-20T01:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681294</loc>
  <lastmod>2026-04-20T01:29:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attention-based Adversarial Autoencoderによるマルチスケールネットワーク埋め込み（AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding）</news:title>
   <news:publication_date>2026-04-20T01:29:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681292</loc>
  <lastmod>2026-04-20T01:29:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>写真のソーシャルメタデータから場所の景観美を予測できるか（Can We Predict the Scenic Beauty of Locations from Geo-tagged Flickr Images?）</news:title>
   <news:publication_date>2026-04-20T01:29:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681290</loc>
  <lastmod>2026-04-20T00:38:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小改変でCNNを欺く画像ステガノグラフィ（CNN Based Adversarial Embedding with Minimum Alteration for Image Steganography）</news:title>
   <news:publication_date>2026-04-20T00:38:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681288</loc>
  <lastmod>2026-04-20T00:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現豊かな音声合成におけるイントネーション転移の実現（Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron）</news:title>
   <news:publication_date>2026-04-20T00:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681286</loc>
  <lastmod>2026-04-20T00:37:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ推定における制約の滑らかさの重要性（The Importance of Constraint Smoothness for Parameter Estimation in Computational Cognitive Modeling）</news:title>
   <news:publication_date>2026-04-20T00:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681284</loc>
  <lastmod>2026-04-20T00:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現を学習する「スタイルトークン」――エンドツーエンド音声合成の制御と転送 (Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis)</news:title>
   <news:publication_date>2026-04-20T00:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681282</loc>
  <lastmod>2026-04-20T00:37:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットに「説明書」を付ける考え方（Datasheets for Datasets）</news:title>
   <news:publication_date>2026-04-20T00:37:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681280</loc>
  <lastmod>2026-04-20T00:36:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上でのハイブリッド高速畳み込みによる顔認識高速化（Face Recognition with Hybrid Efficient Convolution Algorithms on FPGAs）</news:title>
   <news:publication_date>2026-04-20T00:36:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681278</loc>
  <lastmod>2026-04-20T00:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現転移学習による顔認識の少数サンプル問題への対処（Feature Transfer Learning for Face Recognition with Under-Represented Data）</news:title>
   <news:publication_date>2026-04-20T00:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681276</loc>
  <lastmod>2026-04-19T23:46:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Successor Representationを用いたGVFにおける学習加速（Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation）</news:title>
   <news:publication_date>2026-04-19T23:46:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681274</loc>
  <lastmod>2026-04-19T23:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層状自己組織化マップによるパターン解析（Pattern Analysis with Layered Self-Organizing Maps）</news:title>
   <news:publication_date>2026-04-19T23:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681272</loc>
  <lastmod>2026-04-19T23:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復低ランク近似によるCNN圧縮（Iterative Low-Rank Approximation for CNN Compression）</news:title>
   <news:publication_date>2026-04-19T23:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681270</loc>
  <lastmod>2026-04-19T23:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文単位の関連フィードバックが高リコール検索を変える（Evaluating Sentence-Level Relevance Feedback for High-Recall Information Retrieval）</news:title>
   <news:publication_date>2026-04-19T23:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681268</loc>
  <lastmod>2026-04-19T23:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMood：携帯文字入力の振る舞いから感情状態を推定する手法（DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection）</news:title>
   <news:publication_date>2026-04-19T23:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681266</loc>
  <lastmod>2026-04-19T23:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈外エラー検出の自動評価法（Automated Evaluation of Out-of-Context Errors）</news:title>
   <news:publication_date>2026-04-19T23:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681264</loc>
  <lastmod>2026-04-19T23:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フェーズ分離を学習する深層学習（Deep Learning Phase Segregation）</news:title>
   <news:publication_date>2026-04-19T23:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681262</loc>
  <lastmod>2026-04-19T22:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘルスケアのためのBroad Learning（Broad Learning for Healthcare）</news:title>
   <news:publication_date>2026-04-19T22:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681260</loc>
  <lastmod>2026-04-19T22:53:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-19T22:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681258</loc>
  <lastmod>2026-04-19T22:52:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から単語埋め込みを学ぶSpeech2Vec（Speech2Vec: A Sequence-to-Sequence Framework for Learning Word Embeddings from Speech）</news:title>
   <news:publication_date>2026-04-19T22:52:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681256</loc>
  <lastmod>2026-04-19T22:52:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALBA製デジタルLLRFを用いたSolaris光源の運用経験（OPERATIONAL EXPERIENCE OF ALBA&amp;#039;S DIGITAL LLRF AT SOLARIS LIGHT SOURCE）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681254</loc>
  <lastmod>2026-04-19T22:52:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック単位手続き的学習とアニーリングした敵対的損失による画像修復（Image Inpainting using Block-wise Procedural Training with Annealed Adversarial Counterpart）</news:title>
   <news:publication_date>2026-04-19T22:52:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681252</loc>
  <lastmod>2026-04-19T22:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDAR深度補完を小さなモデルで実現する圧縮センシングの工夫（Deep Convolutional Compressed Sensing for LiDAR Depth Completion）</news:title>
   <news:publication_date>2026-04-19T22:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-19T22:51:27Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最後の四つの「予想」(Four Last &amp;#039;Conjectures&amp;#039;)</news:title>
   <news:publication_date>2026-04-19T22:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681248</loc>
  <lastmod>2026-04-19T22:00:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強い量子ダーウィニズムと強い独立性はスペクトラム放送構造に相当する（Strong Quantum Darwinism and Strong Independence is equivalent to Spectrum Broadcast Structure）</news:title>
   <news:publication_date>2026-04-19T22:00:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681246</loc>
  <lastmod>2026-04-19T22:00:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>旋削工程におけるチャタ検出を拓く：機械学習とトポロジカルデータ解析の統合 (Chatter Classification in Turning using Machine Learning and Topological Data Analysis)</news:title>
   <news:publication_date>2026-04-19T22:00:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681244</loc>
  <lastmod>2026-04-19T21:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤方偏移6付近における大規模なメタ銀河系電離背景の変動の証拠（Evidence for Large-Scale Fluctuations in the Metagalactic Ionizing Background Near Redshift Six）</news:title>
   <news:publication_date>2026-04-19T21:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681242</loc>
  <lastmod>2026-04-19T21:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水の大容量・長期・深度超冷却を可能にした表面封止法（Long-term deep supercooling of large-volume water via surface sealing with immiscible liquids）</news:title>
   <news:publication_date>2026-04-19T21:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681240</loc>
  <lastmod>2026-04-19T21:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドニューラル上の明示的推論による視覚質問応答（Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering）</news:title>
   <news:publication_date>2026-04-19T21:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681238</loc>
  <lastmod>2026-04-19T21:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイザンチン耐性確率的勾配降下法（Byzantine Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-04-19T21:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681236</loc>
  <lastmod>2026-04-19T21:57:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの非テクスチャ変形面復元の学習（Learning to Reconstruct Texture-less Deformable Surfaces from a Single View）</news:title>
   <news:publication_date>2026-04-19T21:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681234</loc>
  <lastmod>2026-04-19T21:05:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格差嫌悪が長期的な協力を促す仕組み（Inequity aversion improves cooperation in intertemporal social dilemmas）</news:title>
   <news:publication_date>2026-04-19T21:05:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681232</loc>
  <lastmod>2026-04-19T21:05:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Trace your sources in large-scale data（一環で見つける大規模データのソース追跡）</news:title>
   <news:publication_date>2026-04-19T21:05:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681230</loc>
  <lastmod>2026-04-19T21:04:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続と離散が混在する部分観測系に対する動的計画法（Dynamic Programming for POMDP with Jointly Discrete and Continuous State-Spaces）</news:title>
   <news:publication_date>2026-04-19T21:04:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681228</loc>
  <lastmod>2026-04-19T21:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内視鏡単一画像超解像のための効果的深層学習訓練（Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction）</news:title>
   <news:publication_date>2026-04-19T21:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681226</loc>
  <lastmod>2026-04-19T21:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像と音声で出来事を特定する研究（Audio-Visual Event Localization in Unconstrained Videos）</news:title>
   <news:publication_date>2026-04-19T21:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681224</loc>
  <lastmod>2026-04-19T21:03:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声の分布意味論の難しさ（On the difﬁculty of a distributional semantics of spoken language）</news:title>
   <news:publication_date>2026-04-19T21:03:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681222</loc>
  <lastmod>2026-04-19T21:02:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期共有メモリにおける確率的勾配降下法の収束性（The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory）</news:title>
   <news:publication_date>2026-04-19T21:02:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681220</loc>
  <lastmod>2026-04-19T20:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理学者のための機械学習入門（A high-bias, low-variance introduction to Machine Learning for physicists）</news:title>
   <news:publication_date>2026-04-19T20:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681218</loc>
  <lastmod>2026-04-19T20:11:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気シールド対応ハイブリッドトラップで大型ボース＝アインシュタイン凝縮を作る（Production of large Bose-Einstein condensates in a magnetic-shield-compatible hybrid trap）</news:title>
   <news:publication_date>2026-04-19T20:11:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681216</loc>
  <lastmod>2026-04-19T20:10:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローン映像で「実世界の人密度」を推定する仕組み（Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation）</news:title>
   <news:publication_date>2026-04-19T20:10:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681214</loc>
  <lastmod>2026-04-19T20:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サリエンシーを用いた敵対的摂動の検出（Detecting Adversarial Perturbations with Saliency）</news:title>
   <news:publication_date>2026-04-19T20:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681212</loc>
  <lastmod>2026-04-19T20:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮センシングMRIのための深い誤差補正ネットワーク（A Deep Error Correction Network for Compressed Sensing MRI）</news:title>
   <news:publication_date>2026-04-19T20:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681210</loc>
  <lastmod>2026-04-19T20:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システムの因果モデリング（Causal Modeling of Dynamical Systems）</news:title>
   <news:publication_date>2026-04-19T20:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681208</loc>
  <lastmod>2026-04-19T20:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像注釈のための深層コンテキストネットワークアーキテクチャの学習（Learning Deep Context-Network Architectures for Image Annotation）</news:title>
   <news:publication_date>2026-04-19T20:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681206</loc>
  <lastmod>2026-04-19T19:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット向け物体検出の学習を高速化する手法（Speeding-up Object Detection Training for Robotics with FALKON）</news:title>
   <news:publication_date>2026-04-19T19:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681204</loc>
  <lastmod>2026-04-19T19:16:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配列データからタンパク質の構成モチーフを学習する（Learning protein constitutive motifs from sequence data）</news:title>
   <news:publication_date>2026-04-19T19:16:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681202</loc>
  <lastmod>2026-04-19T19:16:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像における一般化と堅牢性の相克（Generalizability vs. Robustness: Adversarial Examples for Medical Imaging）</news:title>
   <news:publication_date>2026-04-19T19:16:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681200</loc>
  <lastmod>2026-04-19T19:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単段検出器と二段階検出器の精度と速度の最適化（Optimizing the Trade-off between Single-Stage and Two-Stage Deep Object Detectors using Image Difficulty Prediction）</news:title>
   <news:publication_date>2026-04-19T19:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681198</loc>
  <lastmod>2026-04-19T19:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるホログラフィック正規化（Holographic Renormalization with Machine learning）</news:title>
   <news:publication_date>2026-04-19T19:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681196</loc>
  <lastmod>2026-04-19T19:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別における姿勢駆動モデルと再ランキングの進展（Pose-Driven Re-Id and Re-Ranking Advances）</news:title>
   <news:publication_date>2026-04-19T19:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681194</loc>
  <lastmod>2026-04-19T19:15:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アラームベースの処方的プロセスモニタリング（Alarm-Based Prescriptive Process Monitoring）</news:title>
   <news:publication_date>2026-04-19T19:15:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681192</loc>
  <lastmod>2026-04-19T18:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時刻の伸縮に強くなるRNNの設計（CAN RECURRENT NEURAL NETWORKS WARP TIME?）</news:title>
   <news:publication_date>2026-04-19T18:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681190</loc>
  <lastmod>2026-04-19T18:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による医用画像セグメンテーションの実用化軸（Deep learning and its application to medical image segmentation）</news:title>
   <news:publication_date>2026-04-19T18:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681188</loc>
  <lastmod>2026-04-19T18:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コアセットのための決定的点過程（Determinantal Point Processes for Coresets）</news:title>
   <news:publication_date>2026-04-19T18:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681186</loc>
  <lastmod>2026-04-19T18:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間時間規則化相関フィルタによる視覚追跡の高速化と頑健化（Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking）</news:title>
   <news:publication_date>2026-04-19T18:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681184</loc>
  <lastmod>2026-04-19T18:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域フィルタリング相関追跡（Region-filtering Correlation Tracking）</news:title>
   <news:publication_date>2026-04-19T18:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681182</loc>
  <lastmod>2026-04-19T18:22:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッドステレオマッチングネットワーク（Pyramid Stereo Matching Network）</news:title>
   <news:publication_date>2026-04-19T18:22:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681180</loc>
  <lastmod>2026-04-19T18:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヤコビアン正則化によるDNNの敵対的耐性向上（Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization）</news:title>
   <news:publication_date>2026-04-19T18:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681178</loc>
  <lastmod>2026-04-19T17:31:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
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 </url>
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 </url>
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 </url>
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 </url>
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 </url>
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 <url>
  <loc>https://aibr.jp/archives/681104</loc>
  <lastmod>2026-04-19T13:00:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Minecraftにおけるモデル学習とモンテカルロ木探索を用いた深層強化学習（Deep Reinforcement Learning with Model Learning and Monte Carlo Tree Search in Minecraft）</news:title>
   <news:publication_date>2026-04-19T13:00:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681102</loc>
  <lastmod>2026-04-19T12:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話エージェントの急速な変化（The Rapidly Changing Landscape of Conversational Agents）</news:title>
   <news:publication_date>2026-04-19T12:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681100</loc>
  <lastmod>2026-04-19T12:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイド付き画像インペインティング（Guided Image Inpainting: Replacing an Image Region by Pulling Content from Another Image）</news:title>
   <news:publication_date>2026-04-19T12:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681098</loc>
  <lastmod>2026-04-19T12:59:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を幾何学で解きほぐす：反復射影のアプローチ（DEMYSTIFYING DEEP LEARNING: A GEOMETRIC APPROACH TO ITERATIVE PROJECTIONS）</news:title>
   <news:publication_date>2026-04-19T12:59:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681096</loc>
  <lastmod>2026-04-19T12:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非可換モノポールとQCDにおける閉じ込めとXSB（Confinement and XSB in QCD: Mysteries and beauty of soliton dynamics in nonAbelian gauge theories）</news:title>
   <news:publication_date>2026-04-19T12:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681094</loc>
  <lastmod>2026-04-19T12:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロヒンギャ関連コメントの感情分析に関するSVM研究（Sentiment Analysis of Comments on Rohingya Movement with Support Vector Machine）</news:title>
   <news:publication_date>2026-04-19T12:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681092</loc>
  <lastmod>2026-04-19T12:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PlaneMatchによる平面コプラナリ予測で堅牢なRGB-D再構成を実現する（PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction）</news:title>
   <news:publication_date>2026-04-19T12:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681090</loc>
  <lastmod>2026-04-19T12:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部焦点化タイムディスタンス・ヘリオセイズモロジーにおける伝播時間と振幅測定の比較（Comparison of Travel-Time and Amplitude Measurements for Deep-Focusing Time–Distance Helioseismology）</news:title>
   <news:publication_date>2026-04-19T12:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681088</loc>
  <lastmod>2026-04-19T12:06:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>濃密接続ピラミッド除霧ネットワークの要点（Densely Connected Pyramid Dehazing Network）</news:title>
   <news:publication_date>2026-04-19T12:06:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681086</loc>
  <lastmod>2026-04-19T12:06:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DOP: 近似価値評価を用いた深い楽観的計画（DOP: Deep Optimistic Planning with Approximate Value Function Evaluation）</news:title>
   <news:publication_date>2026-04-19T12:06:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681084</loc>
  <lastmod>2026-04-19T12:06:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類層におけるReLUの応用—出力層を直線化する試み（Deep Learning using Rectified Linear Units (ReLU))</news:title>
   <news:publication_date>2026-04-19T12:06:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681082</loc>
  <lastmod>2026-04-19T12:05:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミラー層化正則化によるモデル整合性の理論的整理（Model Consistency for Learning with Mirror-Stratifiable Regularizers）</news:title>
   <news:publication_date>2026-04-19T12:05:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681080</loc>
  <lastmod>2026-04-19T11:14:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化出力の放棄学習による意見予測の精度向上（Structured Output Learning with Abstention: Application to Accurate Opinion Prediction）</news:title>
   <news:publication_date>2026-04-19T11:14:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681078</loc>
  <lastmod>2026-04-19T11:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gradient DescentがReLUネットワーク特徴を量子化する（Gradient Descent Quantizes ReLU Network Features）</news:title>
   <news:publication_date>2026-04-19T11:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681076</loc>
  <lastmod>2026-04-19T11:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>隠れパラメータの決定的割当による学習（Learning through deterministic assignment of hidden parameters）</news:title>
   <news:publication_date>2026-04-19T11:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681074</loc>
  <lastmod>2026-04-19T11:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学データから銀河の中性水素量を予測する機械学習（Predicting the Neutral Hydrogen Content of Galaxies From Optical Data Using Machine Learning）</news:title>
   <news:publication_date>2026-04-19T11:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681072</loc>
  <lastmod>2026-04-19T11:13:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部流体注入に伴う誘発地震に対する自律的意思決定（Autonomous decision-making against induced seismicity in deep fluid injections）</news:title>
   <news:publication_date>2026-04-19T11:13:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681070</loc>
  <lastmod>2026-04-19T11:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワークは何を見ているか（What do Deep Networks Like to See?）</news:title>
   <news:publication_date>2026-04-19T11:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681068</loc>
  <lastmod>2026-04-19T11:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>優先度付きマルチビュー深度マップ生成と信頼度予測（Prioritized Multi-View Stereo Depth Map Generation Using Confidence Prediction）</news:title>
   <news:publication_date>2026-04-19T11:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681066</loc>
  <lastmod>2026-04-19T10:22:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光モードの場分布を機械学習で分類する手法（Machine learning classification for field distributions of photonic modes）</news:title>
   <news:publication_date>2026-04-19T10:22:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681064</loc>
  <lastmod>2026-04-19T10:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子イジング臨界付近のクエンチとニューラルネットワークの限界（Quenches near Ising quantum criticality as a challenge for artificial neural networks）</news:title>
   <news:publication_date>2026-04-19T10:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681062</loc>
  <lastmod>2026-04-19T10:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>がん臨床試験における適格判定を自動化する手法（Learning Eligibility in Cancer Clinical Trials using Deep Neural Networks）</news:title>
   <news:publication_date>2026-04-19T10:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681060</loc>
  <lastmod>2026-04-19T10:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見えない関節を仮想世界で学習して検出・追跡する技術（Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World）</news:title>
   <news:publication_date>2026-04-19T10:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681058</loc>
  <lastmod>2026-04-19T10:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>永続エントロピーの安定性と要約関数の提案（On the stability of persistent entropy and new summary functions for Topological Data Analysis）</news:title>
   <news:publication_date>2026-04-19T10:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681056</loc>
  <lastmod>2026-04-19T10:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全な探索を実現する学習型モデル予測制御（Learning-based Model Predictive Control for Safe Exploration）</news:title>
   <news:publication_date>2026-04-19T10:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681054</loc>
  <lastmod>2026-04-19T10:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインソーシャルネットワークにおける偽プロフィールの実態と法的対策（Sneak into Devil’s Colony — Study of Fake Profiles in Online Social Networks and the Cyber Law）</news:title>
   <news:publication_date>2026-04-19T10:18:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681052</loc>
  <lastmod>2026-04-19T09:25:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者クラスタリングにおけるCNNと音声前処理の実践的考察（Speaker Clustering With Neural Networks And Audio Processing）</news:title>
   <news:publication_date>2026-04-19T09:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681050</loc>
  <lastmod>2026-04-19T09:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>緩やかな銀河群における銀河間水素ガスの全容解明（Galaxy interactions in loose galaxy groups: KAT-7 and VLA H i Observations of the IC 1459 group）</news:title>
   <news:publication_date>2026-04-19T09:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681048</loc>
  <lastmod>2026-04-19T09:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D関節情報から学ぶ教師なし3D人体姿勢推定（Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations）</news:title>
   <news:publication_date>2026-04-19T09:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681046</loc>
  <lastmod>2026-04-19T09:24:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PersonLab: 人物の姿勢推定とインスタンス分割を統合するボトムアップ手法（PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model）</news:title>
   <news:publication_date>2026-04-19T09:24:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681044</loc>
  <lastmod>2026-04-19T09:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シャノンのチャネルから意味的チャネルへ（From Shannon’s Channel to Semantic Channel via New Bayes’ Formulas for Machine Learning）</news:title>
   <news:publication_date>2026-04-19T09:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681042</loc>
  <lastmod>2026-04-19T09:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形流体のためのスパース畳み込みに基づくマルコフモデル（Sparse Convolution-based Markov Models for Nonlinear Fluid Flows）</news:title>
   <news:publication_date>2026-04-19T09:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681040</loc>
  <lastmod>2026-04-19T09:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載ネットワークにおける安全なメッセージ伝播の位相的アプローチ (A Topological Approach to Secure Message Dissemination in Vehicular Networks)</news:title>
   <news:publication_date>2026-04-19T09:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681038</loc>
  <lastmod>2026-04-19T08:33:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高品質物体検出のための単発双方向ピラミッドネットワーク（Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection）</news:title>
   <news:publication_date>2026-04-19T08:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681036</loc>
  <lastmod>2026-04-19T08:32:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽性・未ラベル畳み込みニューラルネットワークによるクライオ電子顕微鏡画像の粒子選別（Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs）</news:title>
   <news:publication_date>2026-04-19T08:32:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681034</loc>
  <lastmod>2026-04-19T08:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による低次元化で見える遷移乱流の本質（Construction of low-dimensional system reproducing low-Reynolds-number turbulence）</news:title>
   <news:publication_date>2026-04-19T08:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681032</loc>
  <lastmod>2026-04-19T08:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一相の性質から複数の相転移を予測する機械学習（Extrapolating quantum observables with machine learning: Inferring multiple phase transitions from properties of a single phase）</news:title>
   <news:publication_date>2026-04-19T08:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681030</loc>
  <lastmod>2026-04-19T08:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residual Networksの安定性と凸/凹分解が示す学習の本質（Residual Networks: Lyapunov Stability and Convex Decomposition）</news:title>
   <news:publication_date>2026-04-19T08:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681028</loc>
  <lastmod>2026-04-19T08:31:27Z</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3D人体姿勢推定を変える手法（Deep Pose Consensus Networks）</news:title>
   <news:publication_date>2026-04-19T08:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681026</loc>
  <lastmod>2026-04-19T08:30:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曲率情報を用いた確率的分散最適化の加速（SUCAG: Stochastic Unbiased Curvature-aided Gradient Method for Distributed Optimization）</news:title>
   <news:publication_date>2026-04-19T08:30:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681024</loc>
  <lastmod>2026-04-19T07:40:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANに制約を直接組み込む手法とその実用性（Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-19T07:40:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681022</loc>
  <lastmod>2026-04-19T07:39:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDARとカメラの外部較正を自己学習で解く（CalibNet: Geometrically Supervised Extrinsic Calibration using 3D Spatial Transformer Networks）</news:title>
   <news:publication_date>2026-04-19T07:39:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681020</loc>
  <lastmod>2026-04-19T07:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復ブースティングによる確率密度推定の再考（Boosted Density Estimation Remastered）</news:title>
   <news:publication_date>2026-04-19T07:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681018</loc>
  <lastmod>2026-04-19T07:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるホログラフィック像復元の焦点拡張（Extended depth-of-field in holographic image reconstruction using deep learning based auto-focusing and phase-recovery）</news:title>
   <news:publication_date>2026-04-19T07:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681016</loc>
  <lastmod>2026-04-19T07:38:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力ごとの反復計算を問う：Repeat‑RNNとACTの比較（Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-04-19T07:38:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681014</loc>
  <lastmod>2026-04-19T07:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指紋ベース屋内位置推定の学習関数（Learning the Localization Function）</news:title>
   <news:publication_date>2026-04-19T07:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681012</loc>
  <lastmod>2026-04-19T07:37:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検閲データからの誤学習（Mislearning from Censored Data: The Gambler’s Fallacy and Other Correlational Mistakes in Optimal-Stopping Problems）</news:title>
   <news:publication_date>2026-04-19T07:37:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681010</loc>
  <lastmod>2026-04-19T06:47:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健なブラインドデコンボリューションとMirror Descent（Robust Blind Deconvolution via Mirror Descent）</news:title>
   <news:publication_date>2026-04-19T06:47:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681008</loc>
  <lastmod>2026-04-19T06:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク依存深層LDAプルーニング（Task-dependent Deep LDA pruning of neural networks）</news:title>
   <news:publication_date>2026-04-19T06:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681006</loc>
  <lastmod>2026-04-19T06:46:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seglearnによる時系列学習の実務活用（Seglearn: A Python Package for Learning Sequences and Time Series）</news:title>
   <news:publication_date>2026-04-19T06:46:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681004</loc>
  <lastmod>2026-04-19T06:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>速度変化に頑強な埋め込み学習（T-RECS: Training for Rate-Invariant Embeddings by Controlling Speed for Action Recognition）</news:title>
   <news:publication_date>2026-04-19T06:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681002</loc>
  <lastmod>2026-04-19T06:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点・多クラス物体姿勢推定の統一フレームワーク（A Unified Framework for Multi-View Multi-Class Object Pose Estimation）</news:title>
   <news:publication_date>2026-04-19T06:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681000</loc>
  <lastmod>2026-04-19T06:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラッタ中の操作におけるリセディングホライズン計画と学習価値関数（Planning with a Receding Horizon for Manipulation in Clutter using a Learned Value Function）</news:title>
   <news:publication_date>2026-04-19T06:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680998</loc>
  <lastmod>2026-04-19T06:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間データ圧縮の実務的手法──密度ベースクラスタリングによる代表点抽出（Clustering to Reduce Spatial Data Set Size）</news:title>
   <news:publication_date>2026-04-19T06:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680996</loc>
  <lastmod>2026-04-19T05:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>黒洞の鐘（A Carillon of Black Holes）</news:title>
   <news:publication_date>2026-04-19T05:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680994</loc>
  <lastmod>2026-04-19T05:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インクリメンタルな学習を学ぶ—逐次タスクで学習アルゴリズムを最適化する（Incremental Learning-to-Learn with Statistical Guarantees）</news:title>
   <news:publication_date>2026-04-19T05:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680992</loc>
  <lastmod>2026-04-19T05:51:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン投票時における増強されたヒトの影響（Influence of augmented humans in online interactions during voting events）</news:title>
   <news:publication_date>2026-04-19T05:51:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680990</loc>
  <lastmod>2026-04-19T05:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラクタル状プラズモニック自己相似材料の近赤外プラズマ周波数制御（Fractal-like plasmonic self-similar material with a tailorable plasma frequency in the near-infrared）</news:title>
   <news:publication_date>2026-04-19T05:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680988</loc>
  <lastmod>2026-04-19T05:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有分解を使わない深層網の訓練法（Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses）</news:title>
   <news:publication_date>2026-04-19T05:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680986</loc>
  <lastmod>2026-04-19T05:49:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全体属性制御による確率的ビデオ生成（Probabilistic Video Generation using Holistic Attribute Control）</news:title>
   <news:publication_date>2026-04-19T05:49:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680984</loc>
  <lastmod>2026-04-19T05:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェット電荷と機械学習（Jet Charge and Machine Learning）</news:title>
   <news:publication_date>2026-04-19T05:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680982</loc>
  <lastmod>2026-04-19T04:57:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似要素と完全グラフ上のメトリックラベリング（Similar Elements and Metric Labeling on Complete Graphs）</news:title>
   <news:publication_date>2026-04-19T04:57:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680980</loc>
  <lastmod>2026-04-19T04:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散強化学習の双対プライマル解法（Primal-Dual Algorithm for Distributed Reinforcement Learning: Distributed GTD）</news:title>
   <news:publication_date>2026-04-19T04:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680978</loc>
  <lastmod>2026-04-19T04:56:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフと意味埋め込みによるゼロショット認識（Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs）</news:title>
   <news:publication_date>2026-04-19T04:56:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680976</loc>
  <lastmod>2026-04-19T04:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>下部マントルに残るケイ酸塩濃縮領域の持続性（Persistence of Strong Silica-Enriched Domains in the Earth’s Lower Mantle）</news:title>
   <news:publication_date>2026-04-19T04:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680974</loc>
  <lastmod>2026-04-19T04:55:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stacked Cross Attentionによる画像と文の照合（Stacked Cross Attention for Image-Text Matching）</news:title>
   <news:publication_date>2026-04-19T04:55:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680972</loc>
  <lastmod>2026-04-19T04:54:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼深度推定を異種データセットで学ぶ（Monocular Depth Estimation by Learning from Heterogeneous Datasets）</news:title>
   <news:publication_date>2026-04-19T04:54:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680970</loc>
  <lastmod>2026-04-19T04:54:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブートストラップによるランダム化最小二乗法の誤差推定（Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap）</news:title>
   <news:publication_date>2026-04-19T04:54:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680968</loc>
  <lastmod>2026-04-19T04:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力信号を守る防御：Structure-to-Signal Autoencodersによる敵対的防御（Adversarial Defense based on Structure-to-Signal Autoencoders）</news:title>
   <news:publication_date>2026-04-19T04:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680966</loc>
  <lastmod>2026-04-19T04:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-19T04:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680964</loc>
  <lastmod>2026-04-19T04:01:57Z</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バイアス低減のためのワンステップ・ブースト（Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and its Variance Estimate）</news:title>
   <news:publication_date>2026-04-19T04:01:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680962</loc>
  <lastmod>2026-04-19T04:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の情報理論的解釈（Information Theoretic Interpretation of Deep Learning）</news:title>
   <news:publication_date>2026-04-19T04:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680960</loc>
  <lastmod>2026-04-19T04:01:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光ネットワークにおける機械学習の応用概観（An Overview on Application of Machine Learning Techniques in Optical Networks）</news:title>
   <news:publication_date>2026-04-19T04:01:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680958</loc>
  <lastmod>2026-04-19T04:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>嚢胞性線維症における肺異常の定量化（Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks）</news:title>
   <news:publication_date>2026-04-19T04:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680956</loc>
  <lastmod>2026-04-19T04:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグの「自然さ」を再考する：再帰型ニューラルネットワークによる解析（Exploring the Naturalness of Buggy Code with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-04-19T04:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680954</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像の被写界深度にも効く濃霧除去の新潮流（A Cascaded Convolutional Neural Network for Single Image Dehazing）</news:title>
   <news:publication_date>2026-04-19T03:09:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680952</loc>
  <lastmod>2026-04-19T03:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定常ステップサイズ下におけるランダム再シャッフル学習（Stochastic Learning under Random Reshuffling with Constant Step-sizes）</news:title>
   <news:publication_date>2026-04-19T03:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680950</loc>
  <lastmod>2026-04-19T03:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な単調逐次最大化（Resilient Monotone Sequential Maximization）</news:title>
   <news:publication_date>2026-04-19T03:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-19T03:09:06Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>End-to-End Video Captioning with Multitask Reinforcement Learning（End-to-End Video Captioning with Multitask Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-19T03:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680946</loc>
  <lastmod>2026-04-19T03:09:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アイテム選別のためのクラウドと機械の協働（Crowd-Machine Collaboration for Item Screening）</news:title>
   <news:publication_date>2026-04-19T03:09:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680944</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>故障検出性の高いミューテント選択（Selecting Fault Revealing Mutants）</news:title>
   <news:publication_date>2026-04-19T03:08:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680942</loc>
  <lastmod>2026-04-19T03:08:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HATSによるイベントベース画像認識の堅牢化（HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classification）</news:title>
   <news:publication_date>2026-04-19T03:08:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680940</loc>
  <lastmod>2026-04-19T02:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標本画像から種と形質を読み取る試み（Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks）</news:title>
   <news:publication_date>2026-04-19T02:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血液検査から創傷部感染を非教師ありで見抜く多変量時系列カーネル法（An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples）</news:title>
   <news:publication_date>2026-04-19T02:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680936</loc>
  <lastmod>2026-04-19T02:16:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時期依存のエンティティ要素推薦—イベント中心の複数モデル（Multiple Models for Recommending Temporal Aspects of Entities）</news:title>
   <news:publication_date>2026-04-19T02:16:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680934</loc>
  <lastmod>2026-04-19T02:16:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列トピックモデルの拡張とスケーラブル推論（Scalable Generalized Dynamic Topic Models）</news:title>
   <news:publication_date>2026-04-19T02:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680932</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入院再入院予測におけるデータカテゴリの貢献（Contribution of Data Categories to Readmission Prediction Accuracy）</news:title>
   <news:publication_date>2026-04-19T02:16:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680930</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズネットワークの効率的なサンプリングと構造学習（Efficient Sampling and Structure Learning of Bayesian Networks）</news:title>
   <news:publication_date>2026-04-19T02:15:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680928</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列の表現と分類を変えるリザバー・モデル空間（Reservoir computing approaches for representation and classification of multivariate time series）</news:title>
   <news:publication_date>2026-04-19T02:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680926</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Expeditious Generation of Knowledge Graph Embeddings（Expeditious Generation of Knowledge Graph Embeddings）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680924</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル値カーネル空間におけるマルチビュー計量学習 (Multi-view Metric Learning in Vector-valued Kernel Spaces)</news:title>
   <news:publication_date>2026-04-19T01:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680922</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの理論的性質（Some Theoretical Properties of GANs）</news:title>
   <news:publication_date>2026-04-19T01:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680920</loc>
  <lastmod>2026-04-19T01:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周辺分布の一部に高次相関を導入する手法（Introducing higher order correlations to marginals&amp;#039; subset of multivariate data by means of Archimedean copulas）</news:title>
   <news:publication_date>2026-04-19T01:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680918</loc>
  <lastmod>2026-04-19T01:19:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>骨格データとResNetによる行動認識の実装と意義（Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks）</news:title>
   <news:publication_date>2026-04-19T01:19:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680916</loc>
  <lastmod>2026-04-19T01:18:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>骨格データからの行動認識における深層残差ネットワークの活用（Exploiting deep residual networks for human action recognition from skeletal data）</news:title>
   <news:publication_date>2026-04-19T01:18:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680914</loc>
  <lastmod>2026-04-19T01:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>耳認証のドメイン適応と二段階ファインチューニング（Domain Adaptation for Ear Recognition using Deep CNNs）</news:title>
   <news:publication_date>2026-04-19T01:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680912</loc>
  <lastmod>2026-04-19T00:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース系同定のサンプル複雑性（Sample Complexity of Sparse System Identification Problem）</news:title>
   <news:publication_date>2026-04-19T00:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680910</loc>
  <lastmod>2026-04-19T00:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを訓練して空間局在を学ばせると格子状表現が自発的に現れる（EMERGENCE OF GRID-LIKE REPRESENTATIONS BY TRAINING RECURRENT NEURAL NETWORKS TO PERFORM SPATIAL LOCALIZATION）</news:title>
   <news:publication_date>2026-04-19T00:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680908</loc>
  <lastmod>2026-04-19T00:27:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ρ-hot辞書埋め込みと二層LSTMによる感情解析の進展（ρ-hot Lexicon Embedding-based Two-level LSTM for Sentiment Analysis）</news:title>
   <news:publication_date>2026-04-19T00:27:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680906</loc>
  <lastmod>2026-04-19T00:26:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型逐次MCMCによる状態とパラメータ同時推定（Adaptive Sequential MCMC for Combined State and Parameter Estimation）</news:title>
   <news:publication_date>2026-04-19T00:26:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680904</loc>
  <lastmod>2026-04-19T00:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>先を見てから飛べ（Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation）</news:title>
   <news:publication_date>2026-04-19T00:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680902</loc>
  <lastmod>2026-04-19T00:26:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNの形状バイアスの検証（Assessing Shape Bias Property of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-19T00:26:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680900</loc>
  <lastmod>2026-04-19T00:26:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PyramidBoxによる文脈支援型シングルショット顔検出の要点（PyramidBox: A Context-assisted Single Shot Face Detector）</news:title>
   <news:publication_date>2026-04-19T00:26:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680898</loc>
  <lastmod>2026-04-18T23:34:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転予測による教師なし表現学習（Unsupervised Representation Learning by Predicting Image Rotations）</news:title>
   <news:publication_date>2026-04-18T23:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680896</loc>
  <lastmod>2026-04-18T23:34:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム初期化で解ける位相復元 — Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval（Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval）</news:title>
   <news:publication_date>2026-04-18T23:34:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680894</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attention on Attention: Visual Question Answeringの注意機構改良がもたらす実務上の示唆（Attention on Attention: Architectures for Visual Question Answering）</news:title>
   <news:publication_date>2026-04-18T23:33:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680892</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Generative Adversarial Talking Head（Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network）</news:title>
   <news:publication_date>2026-04-18T23:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型計算手法：パラメータとオペレータ推定（Data-Driven Computational Methods: Parameter and Operator Estimations）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T23:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T23:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的グラフィカルモデルにおける推論をGNNで学習する（Inference in Probabilistic Graphical Models by Graph Neural Networks）</news:title>
   <news:publication_date>2026-04-18T22:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T22:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T22:41:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全経路観測からの逆最適制御（Inverse Optimal Control from Incomplete Trajectory Observations）</news:title>
   <news:publication_date>2026-04-18T22:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680876</loc>
  <lastmod>2026-04-18T22:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーソナライゼーションに向けた製品特性の記述（Product Characterisation towards Personalisation）</news:title>
   <news:publication_date>2026-04-18T22:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と触覚を融合した3D形状推定による把持・操作の向上（Multi-Modal Geometric Learning for Grasping and Manipulation）</news:title>
   <news:publication_date>2026-04-18T22:40:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680872</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PaaSクラウドのビジネス視点（PaaS Cloud — The Business Perspective）</news:title>
   <news:publication_date>2026-04-18T22:39:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>室温バルク半導体における励起子制御とコヒーレント歪みパルス（Exciton Control in a Room-Temperature Bulk Semiconductor with Coherent Strain Pulses）</news:title>
   <news:publication_date>2026-04-18T21:48:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上での効率的なRNN実装：ブロック巡回行列による圧縮と加速（EFFICIENT RECURRENT NEURAL NETWORKS USING STRUCTURED MATRICES IN FPGAs）</news:title>
   <news:publication_date>2026-04-18T21:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680866</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高相関設計と整列性を持つ回帰問題のグラフベース正則化（Graph-based regularization for regression problems with alignment and highly-correlated designs）</news:title>
   <news:publication_date>2026-04-18T21:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CADから学ぶロボット組立（Learning Robotic Assembly from CAD）</news:title>
   <news:publication_date>2026-04-18T21:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680862</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T21:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680860</loc>
  <lastmod>2026-04-18T21:47:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化EMによるドメイン適応（Domain Adaptation with Randomized Expectation Maximization）</news:title>
   <news:publication_date>2026-04-18T21:47:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680858</loc>
  <lastmod>2026-04-18T21:46:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなサンプリング領域を持つ動的フィルタリング（Dynamic Filtering with Large Sampling Field for ConvNets）</news:title>
   <news:publication_date>2026-04-18T21:46:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680856</loc>
  <lastmod>2026-04-18T20:55:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルロボット応用における深層学習技術の総覧（A Survey of Deep Learning Techniques for Mobile Robot Applications）</news:title>
   <news:publication_date>2026-04-18T20:55:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680854</loc>
  <lastmod>2026-04-18T20:48:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習における十分統計とBurkholder法（Online Learning: Sufficient Statistics and the Burkholder Method）</news:title>
   <news:publication_date>2026-04-18T20:48:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680852</loc>
  <lastmod>2026-04-18T20:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム的弱い教師あり学習によるマルチエージェント軌跡生成（Generating Multi-Agent Trajectories Using Programmatic Weak Supervision）</news:title>
   <news:publication_date>2026-04-18T20:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680850</loc>
  <lastmod>2026-04-18T20:47:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的直感物理理解のベンチマーク：IntPhys 2019（IntPhys 2019: A Benchmark for Visual Intuitive Physics Understanding）</news:title>
   <news:publication_date>2026-04-18T20:47:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680848</loc>
  <lastmod>2026-04-18T20:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑語識別にカーネル学習を用いる方法（UnibucKernel: A kernel-based learning method for complex word identification）</news:title>
   <news:publication_date>2026-04-18T20:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680846</loc>
  <lastmod>2026-04-18T20:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列補完のLeave-One-Out解析（Leave-one-out Approach for Matrix Completion: Primal and Dual Analysis）</news:title>
   <news:publication_date>2026-04-18T20:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680844</loc>
  <lastmod>2026-04-18T20:46:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天体重力レンズとしての全天監視データ活用とそのインパクト（Gravitationally Lensed Quasars in Gaia: II. Discovery of 24 Lensed Quasars）</news:title>
   <news:publication_date>2026-04-18T20:46:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680842</loc>
  <lastmod>2026-04-18T19:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数ガウス過程によるメタ強化学習（Meta Reinforcement Learning with Latent Variable Gaussian Processes）</news:title>
   <news:publication_date>2026-04-18T19:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680840</loc>
  <lastmod>2026-04-18T19:53:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元学習を探る：罰則付き確率的主成分分析による次元推定（Exploring dimension learning via a penalized probabilistic principal component analysis）</news:title>
   <news:publication_date>2026-04-18T19:53:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680838</loc>
  <lastmod>2026-04-18T19:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリ固有メッシュ再構築の学習（Learning Category-Specific Mesh Reconstruction from Image Collections）</news:title>
   <news:publication_date>2026-04-18T19:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680836</loc>
  <lastmod>2026-04-18T19:52:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有界次数DAGにおけるブロードキャスト（Broadcasting on Bounded Degree DAGs）</news:title>
   <news:publication_date>2026-04-18T19:52:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680834</loc>
  <lastmod>2026-04-18T19:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>p波相互作用フェルミ気体における三体散逸のユニタリ制限挙動（Unitarity-limited behavior of three-body collisions in a p-wave interacting Fermi gas）</news:title>
   <news:publication_date>2026-04-18T19:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680832</loc>
  <lastmod>2026-04-18T19:52:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線毛運動解析のためのスタック型ニューラルネットワーク（STACKED NEURAL NETWORKS FOR END-TO-END CILIARY MOTION ANALYSIS）</news:title>
   <news:publication_date>2026-04-18T19:52:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680830</loc>
  <lastmod>2026-04-18T19:52:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明を求める権利からより良い意思決定の権利へ（Enslaving the Algorithm: From a “Right to an Explanation” to a “Right to Better Decisions”?）</news:title>
   <news:publication_date>2026-04-18T19:52:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680828</loc>
  <lastmod>2026-04-18T19:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース内学習AC/DCの実務的意義（AC/DC: In-Database Learning Thunderstruck）</news:title>
   <news:publication_date>2026-04-18T19:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680826</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステレオと単眼深度推定の自己教師学習による融合（Fusion of stereo and still monocular depth estimates）</news:title>
   <news:publication_date>2026-04-18T18:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680824</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的価格設定と競争環境での学習（Dynamic Pricing and Learning with Competition: Insights from the Dynamic Pricing Challenge）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680822</loc>
  <lastmod>2026-04-18T18:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepGaugeが示す深層学習テストの定量基準（DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems）</news:title>
   <news:publication_date>2026-04-18T18:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680820</loc>
  <lastmod>2026-04-18T18:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然勾配を用いた深層Q学習（Natural Gradient Deep Q-learning）</news:title>
   <news:publication_date>2026-04-18T18:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T18:50:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T17:58:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T17:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/680810</loc>
  <lastmod>2026-04-18T17:58:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLtunerによるトレーニング自動チューニングの実務的意義（MLtuner: System Support for Automatic Machine Learning Tuning）</news:title>
   <news:publication_date>2026-04-18T17:58:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/680808</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースの画像インペインティング（Patch-Based Image Inpainting with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-18T17:57:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680806</loc>
  <lastmod>2026-04-18T17:57:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T17:57:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680804</loc>
  <lastmod>2026-04-18T17:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>VANDELSサーベイが切り拓いた高赤方偏移銀河の深度分光学（The VANDELS spectroscopic survey）</news:title>
   <news:publication_date>2026-04-18T17:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680802</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離志向カーマンフィルタ粒子群最適化法（Distance-Oriented Kalman Filter Particle Swarm Optimizer）</news:title>
   <news:publication_date>2026-04-18T17:56:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680800</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T17:05:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680798</loc>
  <lastmod>2026-04-18T17:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VANDELS ESO公開スペクトロスコピー調査の観測と最初のデータ公開（The VANDELS ESO public spectroscopic survey: observations and first data release）</news:title>
   <news:publication_date>2026-04-18T17:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680796</loc>
  <lastmod>2026-04-18T17:05:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔属性予測のためのResidual Codeanオートエンコーダ（Residual Codean Autoencoder for Facial Attribute Analysis）</news:title>
   <news:publication_date>2026-04-18T17:05:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680794</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分サンプリングで加速するFrank–Wolfe法の実用性（Frank-Wolfe with Subsampling Oracle）</news:title>
   <news:publication_date>2026-04-18T17:04:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680792</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T17:03:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680790</loc>
  <lastmod>2026-04-18T17:03:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層畳み込み特徴の適応共重み付けによる物体検索の改良（Adaptive Co-Weighting Deep Convolutional Features for Object Retrieval）</news:title>
   <news:publication_date>2026-04-18T17:03:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680786</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T16:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680784</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織学画像の自動分割と線維化同定を実現する軽量CNN（Segmentation of histological images and fibrosis identification with a convolutional neural network）</news:title>
   <news:publication_date>2026-04-18T16:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680782</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T16:11:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680780</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層学習における交絡因子除去が医療予測を改善する仕組み（Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications）</news:title>
   <news:publication_date>2026-04-18T16:09:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T16:09:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680774</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680772</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T15:17:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680770</loc>
  <lastmod>2026-04-18T15:16:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T15:16:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680768</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680766</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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