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Expressivity and Approximation Properties of Deep Neural Networks with
  ReLU$^k$ Activation

Expressivity and Approximation Properties of Deep Neural Networks with ReLUk^kk Activation

27 December 2023
Juncai He
Tong Mao
Jinchao Xu
ArXivPDFHTML

Papers citing "Expressivity and Approximation Properties of Deep Neural Networks with ReLU$^k$ Activation"

6 / 6 papers shown
Title
Variational formulation based on duality to solve partial differential equations: Use of B-splines and machine learning approximants
Variational formulation based on duality to solve partial differential equations: Use of B-splines and machine learning approximants
N. Sukumar
Amit Acharya
81
2
0
02 Dec 2024
Deep Neural Networks and Finite Elements of Any Order on Arbitrary
  Dimensions
Deep Neural Networks and Finite Elements of Any Order on Arbitrary Dimensions
Juncai He
Jinchao Xu
15
7
0
21 Dec 2023
Encoding of data sets and algorithms
Encoding of data sets and algorithms
Katarina Z. Doctor
Tong Mao
H. Mhaskar
11
2
0
02 Mar 2023
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Zuowei Shen
Haizhao Yang
Shijun Zhang
79
114
0
28 Feb 2021
Theory of Deep Convolutional Neural Networks II: Spherical Analysis
Theory of Deep Convolutional Neural Networks II: Spherical Analysis
Zhiying Fang
Han Feng
Shuo Huang
Ding-Xuan Zhou
29
37
0
28 Jul 2020
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions
  with $ \ell^1 $ and $ \ell^0 $ Controls
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with ℓ1 \ell^1 ℓ1 and ℓ0 \ell^0 ℓ0 Controls
Jason M. Klusowski
Andrew R. Barron
108
142
0
26 Jul 2016
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