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Elementary superexpressive activations

Elementary superexpressive activations

22 February 2021
Dmitry Yarotsky
ArXivPDFHTML

Papers citing "Elementary superexpressive activations"

10 / 10 papers shown
Title
Don't Fear Peculiar Activation Functions: EUAF and Beyond
Don't Fear Peculiar Activation Functions: EUAF and Beyond
Qianchao Wang
Shijun Zhang
Dong Zeng
Zhaoheng Xie
Hengtao Guo
Feng-Lei Fan
Tieyong Zeng
42
3
0
12 Jul 2024
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of
  Experts
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts
Anastasis Kratsios
Haitz Sáez de Ocáriz Borde
Takashi Furuya
Marc T. Law
MoE
41
1
0
05 Feb 2024
Neural Network Approximation for Pessimistic Offline Reinforcement
  Learning
Neural Network Approximation for Pessimistic Offline Reinforcement Learning
Di Wu
Yuling Jiao
Li Shen
Haizhao Yang
Xiliang Lu
OffRL
29
1
0
19 Dec 2023
Expressive power of binary and ternary neural networks
Expressive power of binary and ternary neural networks
A. Beknazaryan
MQ
19
0
0
27 Jun 2022
Finite Expression Method for Solving High-Dimensional Partial
  Differential Equations
Finite Expression Method for Solving High-Dimensional Partial Differential Equations
Senwei Liang
Haizhao Yang
34
18
0
21 Jun 2022
Designing Universal Causal Deep Learning Models: The Geometric
  (Hyper)Transformer
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer
Beatrice Acciaio
Anastasis Kratsios
G. Pammer
OOD
52
20
0
31 Jan 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional
  Spaces
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces
Hao Liu
Haizhao Yang
Minshuo Chen
T. Zhao
Wenjing Liao
32
36
0
01 Jan 2022
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed
  Number of Neurons
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons
Zuowei Shen
Haizhao Yang
Shijun Zhang
56
36
0
06 Jul 2021
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
101
115
0
28 Feb 2021
Phase Transitions in Rate Distortion Theory and Deep Learning
Phase Transitions in Rate Distortion Theory and Deep Learning
Philipp Grohs
Andreas Klotz
F. Voigtlaender
14
7
0
03 Aug 2020
1