Papers

• Emergent contagion complexity: Disentangling mechanistic complexity from correlated heterogeneity (2026)
  Katerina Tang et al.
  5.84
• Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation (2026)
  Guoming Li et al.
  3.34
• From Score Matching to Diffusion: A Fine-Grained Error Analysis in the Gaussian Setting (2026)
  Samuel Hurault et al.
  1.89
• Differential-Integral Neural Operator for Long-Term Turbulence Forecasting (2026)
  Hao Wu et al.
  1.89
• TEA-Time: Transporting Effects Across Time (2026)
  Harsh Parikh et al.
  1.89
• Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks (2017)
  Federico Monti et al.
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• Efficient Model-Based Collaborative Filtering with Fast Adaptive PCA (2020)
  Xiangyun Ding et al.
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• Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale (2021)
  Zhaoxia (Summer) Deng et al.
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• A Matrix Decomposition Model Based on Feature Factors in Movie Recommendation System (2022)
  Dan Liu and Hou-biao Li
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• Multi-Metric AutoRec for High Dimensional and Sparse User Behavior Data Prediction (2022)
  Cheng Liang et al.
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• Improving Recommendation Relevance by simulating User Interest (2023)
  Alexander Kushkuley and Joshua Correa
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