Towards a Mathematical Understanding of Neural Network-Based Machine Learning: What We Know and What We Don't-Reference-Cited by-同舟云学术

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Towards a Mathematical Understanding of Neural Network-Based Machine Learning: What We Know and What We Don't

Published:2020-06 Issue:4 Volume:1 Page:561-615
ISSN:2708-0560
Container-title:CSIAM Transactions on Applied Mathematics
language:
Short-container-title:CSIAM-AM

Author:

E Weinan

Publisher

Global Science Press

Subject

General Medicine

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Energetic Variational Neural Network Discretizations of Gradient Flows;SIAM Journal on Scientific Computing;2024-08-05

2. A Reduced Order Schwarz Method for Nonlinear Multiscale Elliptic Equations Based on Two-Layer Neural Networks;Journal of Computational Mathematics;2024-06

3. Infinite‐width limit of deep linear neural networks;Communications on Pure and Applied Mathematics;2024-05-06

4. Conditioning of random Fourier feature matrices: double descent and generalization error;Information and Inference: A Journal of the IMA;2024-04-01

5. Overall error analysis for the training of deep neural networks via stochastic gradient descent with random initialisation;Applied Mathematics and Computation;2023-10

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