Characterization of the Variation Spaces Corresponding to Shallow Neural Networks

28 June 2021

Papers citing "Characterization of the Variation Spaces Corresponding to Shallow Neural Networks"

12 / 12 papers shown

Title
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities Rahul Parhi Michael Unser 61 5 0 05 Oct 2023
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks Jonathan W. Siegel 67 7 0 28 Jul 2023
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory Rahul Parhi Robert D. Nowak MLT 48 71 0 07 May 2021
Sharp Bounds on the Approximation Rates, Metric Entropy, and $n$ -widths of Shallow Neural Networks Jonathan W. Siegel Jinchao Xu 45 87 0 29 Jan 2021
Complexity Measures for Neural Networks with General Activation Functions Using Path-based Norms Zhong Li Chao Ma Lei Wu 38 24 0 14 Sep 2020
Representation formulas and pointwise properties for Barron functions E. Weinan Stephan Wojtowytsch 41 80 0 10 Jun 2020
Neural network integral representations with the ReLU activation function Armenak Petrosyan Anton Dereventsov Clayton Webster 32 22 0 07 Oct 2019
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case Greg Ongie Rebecca Willett Daniel Soudry Nathan Srebro 24 160 0 03 Oct 2019
The Barron Space and the Flow-induced Function Spaces for Neural Network Models E. Weinan Chao Ma Lei Wu 56 110 0 18 Jun 2019
How do infinite width bounded norm networks look in function space? Pedro H. P. Savarese Itay Evron Daniel Soudry Nathan Srebro 42 166 0 13 Feb 2019
$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 $\ell^1$ and $\ell^0$ Controls Jason M. Klusowski Andrew R. Barron 200 143 0 26 Jul 2016
Approximation and learning by greedy algorithms Andrew R. Barron A. Cohen W. Dahmen Ronald A. DeVore 86 320 0 12 Mar 2008