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  • Reinforcement Learning with Function Approximation: From Linear to Nonlinear

    Jihao Long, Jiequn Han
    2023-09-25
    56050 4694 Pages:161-193 Open-access
  • Bridging Traditional and Machine Learning-Based Algorithms for Solving PDEs: The Random Feature Method

    Jingrun Chen, Xurong Chi, Weinan E, Zhouwang Yang
    2022-09-22
    47136 4774 Pages:268-298 Open-access
  • Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms

    Robert Balkin, Hector D. Ceniceros, Ruimeng Hu
    2024-03-21
    26108 2711 Pages:23-63 Open-access
  • Reinforcement Learning Algorithm for Mixed Mean Field Control Games

    Andrea Angiuli, Nils Detering, Jean-Pierre Fouque, Mathieu Laurière, Jimin Lin
    2023-06-06
    32232 4066 Pages:108-137 Open-access
  • Interpolating Between BSDEs and PINNs: Deep Learning for Elliptic and Parabolic Boundary Value Problems

    Nikolas Nüsken, Lorenz Richter
    2024-03-21
    35999 4570 Pages:31-64 Open-access
  • A Note on Continuous-Time Online Learning

    Lexing Ying
    2025-03-12
    10977 971 Pages:1-10 Open-access
  • Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces

    Andrea Angiuli, Jean-Pierre Fouque, Ruimeng Hu, Alan Raydan
    2025-03-12
    11271 1091 Pages:11-47 Open-access
  • On the Existence of Global Minima and Convergence Analyses for Gradient Descent Methods in the Training of Deep Neural Networks

    Arnulf Jentzen, Adrian Riekert
    2022-07-06
    41390 4206 Pages:141-246 Open-access
  • Perturbational Complexity by Distribution Mismatch: A Systematic Analysis of Reinforcement Learning in Reproducing Kernel Hilbert Space

    Jihao Long, Jiequn Han
    2024-03-21
    80140 4358 Pages:1-37 Open-access
  • A Brief Survey on the Approximation Theory for Sequence Modelling

    Haotian Jiang, Qianxiao Li, Zhong Li, Shida Wang
    2024-03-21
    67224 5283 Pages:1-30 Open-access
  • RNN-Attention Based Deep Learning for Solving Inverse Boundary Problems in Nonlinear Marshak Waves

    Di Zhao, Weiming Li, Wengu Chen, Peng Song, Han Wang
    2023-06-06
    32825 4105 Pages:83-107 Open-access
  • Enhancing Accuracy in Deep Learning Using Random Matrix Theory

    Leonid Berlyand, Etienne Sandier, Yitzchak Shmalo, Lei Zhang
    2024-11-07
    18826 2352 Pages:347-412 Open-access
  • Variational Formulations of ODE-Net as a Mean-Field Optimal Control Problem and Existence Results

    Noboru Isobe, Mizuho Okumura
    2024-11-07
    17621 2016 Pages:413-444 Open-access
  • Progressive Optimal Path Sampling for Closed-Loop Optimal Control Design with Deep Neural Networks

    Xuanxi Zhang, Jihao Long, Wei Hu, Weinan E, Jiequn Han
    2025-10-31
    478 115
  • A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions

    Elisa Negrini, Yuxuan Liu, Liu Yang, Stanley J. Osher, Hayden Schaeffer
    2025-11-14
    118 12
  • DeePN$^2$: A Deep Learning-Based Non-Newtonian Hydrodynamic Model

    Lidong Fang, Pei Ge, Lei Zhang, Weinan E, Huan Lei
    2024-03-21
    81644 5539 Pages:114-140 Open-access
  • Convergence Analysis of Discrete Diffusion Model: Exact Implementation Through Uniformization

    Hongrui Chen, Lexing Ying
    2025-06-03
    8373 724 Pages:108-127 Open-access
  • A Mathematical Framework for Learning Probability Distributions

    Hongkang Yang
    2022-12-30
    36096 4360 Pages:373-431 Open-access
  • Mean-Field Neural Networks-Based Algorithms for McKean-Vlasov Control Problems

    Huyên Pham, Xavier Warin
    2024-06-27
    233 123 Pages:176-214 Open-access
  • Beyond the Quadratic Approximation: The Multiscale Structure of Neural Network Loss Landscapes

    Chao Ma, Daniel Kunin, Lei Wu, Lexing Ying
    2022-09-22
    39259 4444 Pages:247-267 Open-access
  • A Deep Uzawa-Lagrange Multiplier Approach for Boundary Conditions in PINNs and Deep Ritz Methods

    Charalambos G. Makridakis, Aaron Pim, Tristan Pryer
    2025-09-12
    22854 266 Pages:166-191 Open-access
  • Learning a Sparse Representation of Barron Functions with the Inverse Scale Space Flow

    Tjeerd Jan Heeringa, Tim Roith, Christoph Brune, Martin Burger
    2025-03-12
    10927 1105 Pages:48-88 Open-access
  • The Cost-Accuracy Trade-Off in Operator Learning with Neural Networks

    Maarten V. de Hoop, Daniel Zhengyu Huang, Elizabeth Qian, Andrew M. Stuart
    2022-09-22
    40487 4237 Pages:299-341 Open-access
  • Fast Gradient Computation for Gromov-Wasserstein Distance

    Wei Zhang, Zihao Wang, Jie Fan, Hao Wu, Yong Zhang
    2024-09-21
    19671 2278 Pages:282-299 Open-access
  • Solving Bivariate Kinetic Equations for Polymer Diffusion Using Deep Learning

    Heng Wang, Weihua Deng
    2024-06-27
    25479 2346 Pages:215-244 Open-access
  • Semi-Supervised Clustering of Sparse Graphs: Crossing the Information-Theoretic Threshold

    Junda Sheng, Thomas Strohmer
    2024-03-21
    25005 2808 Pages:64-106 Open-access
  • A Local Convergence Theory for the Stochastic Gradient Descent Method in Non-Convex Optimization with Non-Isolated Local Minima

    Taehee Ko, Xiantao Li
    2023-06-06
    26126 2446 Pages:138-160 Open-access
1 - 27 of 29 items
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