Search Results

• 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

• 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 Note on Continuous-Time Online Learning

  Lexing Ying

  2025-03-12

  10977 971 Pages:1-10 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

• 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

• 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

• Approximation Results for Gradient Flow Trained Neural Networks

  Gerrit Welper

  2024-06-27

  25011 2369 Pages:107-175 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

• 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

• 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

• 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