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Batch Normalization Orthogonalizes Representations in Deep Random
  Networks

Batch Normalization Orthogonalizes Representations in Deep Random Networks

7 June 2021
Hadi Daneshmand
Amir Joudaki
Francis R. Bach
    OOD
ArXivPDFHTML

Papers citing "Batch Normalization Orthogonalizes Representations in Deep Random Networks"

27 / 27 papers shown
Title
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
Michael Scholkemper
Xinyi Wu
Ali Jadbabaie
Michael T. Schaub
128
7
0
05 Jun 2024
High-Performance Large-Scale Image Recognition Without Normalization
High-Performance Large-Scale Image Recognition Without Normalization
Andrew Brock
Soham De
Samuel L. Smith
Karen Simonyan
VLM
254
514
0
11 Feb 2021
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random
  Features in CNNs
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
Jonathan Frankle
D. Schwab
Ari S. Morcos
56
140
0
29 Feb 2020
A Deep Conditioning Treatment of Neural Networks
A Deep Conditioning Treatment of Neural Networks
Naman Agarwal
Pranjal Awasthi
Satyen Kale
AI4CE
39
16
0
04 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
282
42,038
0
03 Dec 2019
The Normalization Method for Alleviating Pathological Sharpness in Wide
  Neural Networks
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks
Ryo Karakida
S. Akaho
S. Amari
53
41
0
07 Jun 2019
On the Inductive Bias of Neural Tangent Kernels
On the Inductive Bias of Neural Tangent Kernels
A. Bietti
Julien Mairal
53
255
0
29 May 2019
A Mean Field Theory of Batch Normalization
A Mean Field Theory of Batch Normalization
Greg Yang
Jeffrey Pennington
Vinay Rao
Jascha Narain Sohl-Dickstein
S. Schoenholz
49
178
0
21 Feb 2019
Theoretical Analysis of Auto Rate-Tuning by Batch Normalization
Theoretical Analysis of Auto Rate-Tuning by Batch Normalization
Sanjeev Arora
Zhiyuan Li
Kaifeng Lyu
58
131
0
10 Dec 2018
A Convergence Analysis of Gradient Descent for Deep Linear Neural
  Networks
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
Sanjeev Arora
Nadav Cohen
Noah Golowich
Wei Hu
100
284
0
04 Oct 2018
Deep Convolutional Networks as shallow Gaussian Processes
Deep Convolutional Networks as shallow Gaussian Processes
Adrià Garriga-Alonso
C. Rasmussen
Laurence Aitchison
BDL
UQCV
76
269
0
16 Aug 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot
Franck Gabriel
Clément Hongler
193
3,160
0
20 Jun 2018
Understanding Batch Normalization
Understanding Batch Normalization
Johan Bjorck
Carla P. Gomes
B. Selman
Kilian Q. Weinberger
95
603
0
01 Jun 2018
How Does Batch Normalization Help Optimization?
How Does Batch Normalization Help Optimization?
Shibani Santurkar
Dimitris Tsipras
Andrew Ilyas
Aleksander Madry
ODL
73
1,531
0
29 May 2018
Exponential convergence rates for Batch Normalization: The power of
  length-direction decoupling in non-convex optimization
Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization
Jonas Köhler
Hadi Daneshmand
Aurelien Lucchi
M. Zhou
K. Neymeyr
Thomas Hofmann
44
91
0
27 May 2018
Gaussian Process Behaviour in Wide Deep Neural Networks
Gaussian Process Behaviour in Wide Deep Neural Networks
A. G. Matthews
Mark Rowland
Jiri Hron
Richard Turner
Zoubin Ghahramani
BDL
124
553
0
30 Apr 2018
The Emergence of Spectral Universality in Deep Networks
The Emergence of Spectral Universality in Deep Networks
Jeffrey Pennington
S. Schoenholz
Surya Ganguli
44
171
0
27 Feb 2018
Gradient descent with identity initialization efficiently learns
  positive definite linear transformations by deep residual networks
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
Peter L. Bartlett
D. Helmbold
Philip M. Long
69
116
0
16 Feb 2018
Deep Neural Networks as Gaussian Processes
Deep Neural Networks as Gaussian Processes
Jaehoon Lee
Yasaman Bahri
Roman Novak
S. Schoenholz
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
111
1,086
0
01 Nov 2017
Self-Normalizing Neural Networks
Self-Normalizing Neural Networks
Günter Klambauer
Thomas Unterthiner
Andreas Mayr
Sepp Hochreiter
249
2,496
0
08 Jun 2017
Deep Information Propagation
Deep Information Propagation
S. Schoenholz
Justin Gilmer
Surya Ganguli
Jascha Narain Sohl-Dickstein
64
363
0
04 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
639
36,599
0
25 Aug 2016
Layer Normalization
Layer Normalization
Jimmy Lei Ba
J. Kiros
Geoffrey E. Hinton
285
10,412
0
21 Jul 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.4K
192,638
0
10 Dec 2015
Steps Toward Deep Kernel Methods from Infinite Neural Networks
Steps Toward Deep Kernel Methods from Infinite Neural Networks
Tamir Hazan
Tommi Jaakkola
47
83
0
20 Aug 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
354
43,154
0
11 Feb 2015
Exact solutions to the nonlinear dynamics of learning in deep linear
  neural networks
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Andrew M. Saxe
James L. McClelland
Surya Ganguli
ODL
130
1,830
0
20 Dec 2013
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