Disentangling feature and lazy training in deep neural networks

19 June 2019

Papers citing "Disentangling feature and lazy training in deep neural networks"

9 / 9 papers shown

Title
Asymptotics of Wide Networks from Feynman Diagrams Ethan Dyer Guy Gur-Ari 55 114 0 25 Sep 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation Greg Yang 117 286 0 13 Feb 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 82 247 0 18 Jan 2019
A Modern Take on the Bias-Variance Tradeoff in Neural Networks Brady Neal Sarthak Mittal A. Baratin Vinayak Tantia Matthew Scicluna Simon Lacoste-Julien Ioannis Mitliagkas 80 169 0 19 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 192 1,270 0 04 Oct 2018
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 113 1,091 0 01 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 242 8,856 0 25 Aug 2017
Geometry of Optimization and Implicit Regularization in Deep Learning Behnam Neyshabur Ryota Tomioka Ruslan Salakhutdinov Nathan Srebro AI4CE 60 133 0 08 May 2017
Wide Residual Networks Sergey Zagoruyko N. Komodakis 306 7,971 0 23 May 2016