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Approximation capabilities of neural networks on unbounded domains

Approximation capabilities of neural networks on unbounded domains

21 October 2019
Ming-xi Wang
Yang Qu
ArXivPDFHTML

Papers citing "Approximation capabilities of neural networks on unbounded domains"

5 / 5 papers shown
Title
Neural Networks Trained by Weight Permutation are Universal Approximators
Neural Networks Trained by Weight Permutation are Universal Approximators
Yongqiang Cai
Gaohang Chen
Zhonghua Qiao
72
1
0
01 Jul 2024
Minimum width for universal approximation using ReLU networks on compact
  domain
Minimum width for universal approximation using ReLU networks on compact domain
Namjun Kim
Chanho Min
Sejun Park
VLM
29
10
0
19 Sep 2023
Data Topology-Dependent Upper Bounds of Neural Network Widths
Data Topology-Dependent Upper Bounds of Neural Network Widths
Sangmin Lee
Jong Chul Ye
28
0
0
25 May 2023
Minimum Width for Universal Approximation
Minimum Width for Universal Approximation
Sejun Park
Chulhee Yun
Jaeho Lee
Jinwoo Shin
35
122
0
16 Jun 2020
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
153
603
0
14 Feb 2016
1