Universal approximation and model compression for radial neural networks

6 July 2021

Papers citing "Universal approximation and model compression for radial neural networks"

9 / 9 papers shown

Title
Improving Convergence and Generalization Using Parameter Symmetries Bo-Lu Zhao Robert Mansel Gower Robin G. Walters Rose Yu MoMe 33 13 0 22 May 2023
Symmetries, flat minima, and the conserved quantities of gradient flow Bo-Lu Zhao I. Ganev Robin G. Walters Rose Yu Nima Dehmamy 47 16 0 31 Oct 2022
Quiver neural networks I. Ganev Robin G. Walters 39 4 0 26 Jul 2022
Symmetry Teleportation for Accelerated Optimization B. Zhao Nima Dehmamy Robin G. Walters Rose Yu ODL 23 20 0 21 May 2022
Vector Neurons: A General Framework for SO(3)-Equivariant Networks Congyue Deng Or Litany Yueqi Duan A. Poulenard Andrea Tagliasacchi Leonidas J. Guibas 3DPC 111 316 0 25 Apr 2021
Size and Depth Separation in Approximating Benign Functions with Neural Networks Gal Vardi Daniel Reichman T. Pitassi Ohad Shamir 26 7 0 30 Jan 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,027 0 06 Mar 2020
Universal Equivariant Multilayer Perceptrons Siamak Ravanbakhsh 100 48 0 07 Feb 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017