Approximation in shift-invariant spaces with deep ReLU neural networks-Reference-Cited by-同舟云学术

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Approximation in shift-invariant spaces with deep ReLU neural networks

Published:2022-09 Issue: Volume:153 Page:269-281
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Yang Yunfei^ORCID,Li Zhen^ORCID,Wang Yang

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference51 articles.

1. Neural network learning: Theoretical foundations;Anthony,2009

2. Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks;Bartlett;Journal of Machine Learning Research,2019

3. Almost linear VC dimension bounds for piecewise polynomial networks;Bartlett,1999

4. Optimal approximation with sparsely connected deep neural networks;Bölcskei;SIAM Journal on Mathematics of Data Science,2019

5. Approximation by superpositions of a sigmoidal function;Cybenko;Mathematics of Control, Signals, and Systems,1989

Cited by 3 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. Solving PDEs on unknown manifolds with machine learning;Applied and Computational Harmonic Analysis;2024-07

2. Optimal Rates of Approximation by Shallow ReLU$$^k$$ Neural Networks and Applications to Nonparametric Regression;Constructive Approximation;2024-02-26

3. Approximation bounds for norm constrained neural networks with applications to regression and GANs;Applied and Computational Harmonic Analysis;2023-07

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