Search Results

• Approximation Results for Gradient Flow Trained Neural Networks

  Gerrit Welper

  2024-06-27

  25011 2369 Pages:107-175 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

• Batch Normalization Preconditioning for Stochastic Gradient Langevin Dynamics

  Susanna Lange, Wei Deng, Qiang Ye, Guang Lin

  2024-03-21

  33456 4315 Pages:65-82 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

• Approximation of Functionals by Neural Network Without Curse of Dimensionality

  Yahong Yang, Yang Xiang

  2022-12-30

  35337 4236 Pages:342-372 Open-access

• On the Existence of Optimal Shallow Feedforward Networks with ReLU Activation

  Steffen Dereich, Sebastian Kassing

  2024-03-21

  25718 2857 Pages:1-22 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

• 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

• 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

• Embedding Principle: A Hierarchical Structure of Loss Landscape of Deep Neural Networks

  Yaoyu Zhang, Yuqing Li, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu

  2024-03-21

  80348 4413 Pages:60-113 Open-access

• 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

• 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

• Convergence of Stochastic Gradient Descent under a Local Łojasiewicz Condition for Deep Neural Networks

  Jing An, Jianfeng Lu

  2025-06-03

  8323 752 Pages:89-107 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

• Optimistic Estimate Uncovers the Potential of Nonlinear Models

  Yaoyu Zhang, Zhongwang Zhang, Leyang Zhang, Zhiwei Bai, Tao Luo, Zhi-Qin John Xu

  2025-09-12

  22843 270 Pages:192-222 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

• 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

• Embedding Inequalities for Barron-Type Spaces

  Lei Wu

  2023-12-28

  26050 2885 Pages:259-270 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

• Convergence of Stochastic Gradient Descent Schemes for Łojasiewicz-Landscapes

  Steffen Dereich, Sebastian Kassing

  2024-09-21

  19981 2182 Pages:245-281 Open-access