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A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models. arxiv.org/abs/2401.07187
Statistics (Machine Learning) Papers
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Statistics (Machine Learning) Papers
@StatsPapers
New Statistics (Machine Learning) papers from arxiv.org: supervised, unsupervised. Thank you to arXiv for use of its open access interoperability.
- Automated by @PremiumAcctsRandom Matrix Theory for Deep Learning: Beyond Eigenvalues of Linear Models.
- Automated by @PremiumAcctsPotential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics. arxiv.org/abs/1907.07271
- Automated by @PremiumAcctsStatistical and Algorithmic Foundations of Reinforcement Learning. arxiv.org/abs/2507.14444
- Automated by @PremiumAcctsCan a Transformer Represent a Kalman Filter?.
- Automated by @PremiumAcctsUniversal Learning of Nonlinear Dynamics.
- Automated by @PremiumAcctsMonte Carlo Gradient Estimation in Machine Learning. arxiv.org/abs/1906.10652
- Automated by @PremiumAcctsThe Marginal Value of Adaptive Gradient Methods in Machine Learning. arxiv.org/abs/1705.08292
- Automated by @PremiumAcctsLinear Convergence of Diffusion Models Under the Manifold Hypothesis. arxiv.org/abs/2410.09046
- Automated by @PremiumAcctsA Mathematical Perspective On Contrastive Learning.
- Automated by @PremiumAcctsRiemannian Principal Component Analysis. arxiv.org/abs/2506.00226
- Automated by @PremiumAcctsDiffusion Models for Time Series Forecasting: A Survey. arxiv.org/abs/2507.14507
- Automated by @PremiumAcctsRegularization can make diffusion models more efficient. arxiv.org/abs/2502.09151
- Automated by @PremiumAcctsThe No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning.
