Search Results

• Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms

  Robert Balkin, Hector D. Ceniceros, Ruimeng Hu

  2024-03-21

  26248 2832 Pages:23-63 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

  41548 4262 Pages:141-246 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

  44196 715 Pages:166-191 Open-access

• Interpolating Between BSDEs and PINNs: Deep Learning for Elliptic and Parabolic Boundary Value Problems

  Nikolas Nüsken, Lorenz Richter

  2024-03-21

  36192 4647 Pages:31-64 Open-access

• Enhancing Accuracy in Deep Learning Using Random Matrix Theory

  Leonid Berlyand, Etienne Sandier, Yitzchak Shmalo, Lei Zhang

  2024-11-07

  19023 2480 Pages:347-412 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

  47392 4907 Pages:268-298 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

  32949 4209 Pages:83-107 Open-access

• Variational Formulations of ODE-Net as a Mean-Field Optimal Control Problem and Existence Results

  Noboru Isobe, Mizuho Okumura

  2024-11-07

  17828 2123 Pages:413-444 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

  11439 1190 Pages:11-47 Open-access

• DeePN$^2$: A Deep Learning-Based Non-Newtonian Hydrodynamic Model

  Lidong Fang, Pei Ge, Lei Zhang, Weinan E, Huan Lei

  2024-03-21

  81852 5616 Pages:114-140 Open-access

• Stochastic Operator Network: A Stochastic Maximum Principle Based Approach to Operator Learning

  Ryan Bausback, Jingqiao Tang, Lu Lu, Feng Bao, Phuoc-Toan Huynh

  2026-01-28

  109 46

• Solving Bivariate Kinetic Equations for Polymer Diffusion Using Deep Learning

  Heng Wang, Weihua Deng

  2024-06-27

  25663 2463 Pages:215-244 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

  23974 135 Pages:290-317

• 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

  24413 191 Pages:223-263

• A Brief Survey on the Approximation Theory for Sequence Modelling

  Haotian Jiang, Qianxiao Li, Zhong Li, Shida Wang

  2024-03-21

  67351 5354 Pages:1-30 Open-access

• Neural Stochastic Volterra Equations: Learning Path-Dependent Dynamics

  Martin Bergerhausen, David J. Prömel, David Scheffels

  2025-12-17

  23793 129 Pages:264-289