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• Convergence of Stochastic Gradient Descent Schemes for Łojasiewicz-Landscapes

  Steffen Dereich, Sebastian Kassing

  2024-09-21

  20193 2327 Pages:245-281 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

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

  Jing An, Jianfeng Lu

  2025-06-03

  8565 936 Pages:89-107 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

  26266 2620 Pages:138-160 Open-access

• Approximation Results for Gradient Flow Trained Neural Networks

  Gerrit Welper

  2024-06-27

  25201 2568 Pages:107-175 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

• Beyond the Quadratic Approximation: The Multiscale Structure of Neural Network Loss Landscapes

  Chao Ma, Daniel Kunin, Lei Wu, Lexing Ying

  2022-09-22

  39410 4502 Pages:247-267 Open-access