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  • 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
  • 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
    80496 4499 Pages:60-113 Open-access
  • Spectral Neural Networks: Approximation Theory and Optimization Landscape

    Chenghui Li, Rishi Sonthalia, Nicolás García Trillos
    2026-01-06
    123 206
  • 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
  • Batch Normalization Preconditioning for Stochastic Gradient Langevin Dynamics

    Susanna Lange, Wei Deng, Qiang Ye, Guang Lin
    2024-03-21
    33598 4465 Pages:65-82 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
  • On the Existence of Optimal Shallow Feedforward Networks with ReLU Activation

    Steffen Dereich, Sebastian Kassing
    2024-03-21
    25883 2930 Pages:1-22 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
1 - 8 of 8 items
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