Dynamical Isometry: The Missing Ingredient for Neural Network Pruning

Dynamical Isometry: The Missing Ingredient for Neural Network Pruning

12 May 2021

Huan Wang

Papers citing "Dynamical Isometry: The Missing Ingredient for Neural Network Pruning"

4 / 4 papers shown

Title
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,032 0 06 Mar 2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning Alex Renda Jonathan Frankle Michael Carbin 235 383 0 05 Mar 2020
Structured Pruning for Efficient ConvNets via Incremental Regularization Huan Wang Qiming Zhang Yuehai Wang Haoji Hu 3DPC 42 45 0 20 Nov 2018
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 244 350 0 14 Jun 2018