Dynamical Isometry is Achieved in Residual Networks in a Universal Way
for any Activation Function

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Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function

24 September 2018

Stanislaw Jastrzebski

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Papers citing "Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function"

19 / 19 papers shown

Title
Spectrum concentration in deep residual learning: a free probability approach Zenan Ling Xing He Robert C. Qiu 39 21 0 31 Jul 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 304 354 0 14 Jun 2018
The Dynamics of Learning: A Random Matrix Approach Zhenyu Liao Romain Couillet AI4CE 57 43 0 30 May 2018
How to Start Training: The Effect of Initialization and Architecture Boris Hanin David Rolnick 84 255 0 05 Mar 2018
The Emergence of Spectral Universality in Deep Networks Jeffrey Pennington S. Schoenholz Surya Ganguli 64 173 0 27 Feb 2018
Mean Field Residual Networks: On the Edge of Chaos Greg Yang S. Schoenholz 71 194 0 24 Dec 2017
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice Jeffrey Pennington S. Schoenholz Surya Ganguli ODL 43 254 0 13 Nov 2017
Deep Residual Networks and Weight Initialization Masato Taki ODL 46 24 0 09 Sep 2017
Self-Normalizing Neural Networks Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter 470 2,519 0 08 Jun 2017
The Shattered Gradients Problem: If resnets are the answer, then what is the question? David Balduzzi Marcus Frean Lennox Leary J. P. Lewis Kurt Wan-Duo Ma Brian McWilliams ODL 73 406 0 28 Feb 2017
A Random Matrix Approach to Neural Networks Cosme Louart Zhenyu Liao Romain Couillet 68 161 0 17 Feb 2017
Exponential expressivity in deep neural networks through transient chaos Ben Poole Subhaneil Lahiri M. Raghu Jascha Narain Sohl-Dickstein Surya Ganguli 90 595 0 16 Jun 2016
An Analysis of Deep Neural Network Models for Practical Applications A. Canziani Adam Paszke Eugenio Culurciello 90 1,167 0 24 May 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,196 0 16 Mar 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
All you need is a good init Dmytro Mishkin Jirí Matas ODL 94 612 0 19 Nov 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 465 43,341 0 11 Feb 2015
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 263 1,200 0 30 Nov 2014
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks Andrew M. Saxe James L. McClelland Surya Ganguli ODL 188 1,852 0 20 Dec 2013