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Multilayer feedforward networks with a nonpolynomial activation function can approximate any function

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Lower bounds for approximation by MLP neural networks

V. Maiorov and A. Pinkus · 1999

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Approximation theory of the MLP model in neural networks

A. Pinkus · 1999

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Deep learning

Y. LeCun, Y. Bengio, and G. Hinton · 2015

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Deep learning in neural networks: An overview

J. Schmidhuber · 2015

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On the expressive power of deep learning: A tensor analysis

N. Cohen, O. Sharir, and A. Shashua · 2016

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Deep Learning

I. Goodfellow, Y. Bengio, and A. Courville · 2016

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Understanding deep convolutional networks

S. Mallat · 2016

Error bounds for approximations with deep ReLU networks

D. Yarotsky · 2017

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Optimal approximation of piecewise smooth functions using deep ReLU neural networks

P. Petersen and F. Voigtlaender · 2018

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Provable approximation properties for deep neural networks

U. Shaham, A. Cloninger, and R. R. Coifman · 2018

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Universal approximations of invariant maps by neural networks

Original

D. Yarotsky · 2018

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Deep distributed convolutional neural networks: Universality

D.-X. Zhou · 2018

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Optimal approximation with sparsely connected deep neural networks

H. Bölcskei, P. Grohs, G. Kutyniok, and P. Petersen · 2019