Why neural networks find simple solutions: the many regularizers of geometric complexity

27 September 2022

Papers citing "Why neural networks find simple solutions: the many regularizers of geometric complexity"

5 / 5 papers shown

Title
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 75 18 0 04 Mar 2024
Deep Double Descent via Smooth Interpolation Matteo Gamba Erik Englesson Marten Bjorkman Hossein Azizpour 46 11 0 21 Sep 2022
Stochastic Training is Not Necessary for Generalization Jonas Geiping Micah Goldblum Phillip E. Pope Michael Moeller Tom Goldstein 76 67 0 29 Sep 2021
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 223 2,990 0 24 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 270 2,696 0 15 Sep 2016