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Understanding Batch Normalization
v1v2v3v4 (latest)

Understanding Batch Normalization

1 June 2018
Johan Bjorck
Carla P. Gomes
B. Selman
Kilian Q. Weinberger
ArXiv (abs)PDFHTML

Papers citing "Understanding Batch Normalization"

50 / 224 papers shown
Title
Group Whitening: Balancing Learning Efficiency and Representational
  Capacity
Group Whitening: Balancing Learning Efficiency and Representational Capacity
Lei Huang
Yi Zhou
Li Liu
Fan Zhu
Ling Shao
108
22
0
28 Sep 2020
Normalization Techniques in Training DNNs: Methodology, Analysis and
  Application
Normalization Techniques in Training DNNs: Methodology, Analysis and Application
Lei Huang
Jie Qin
Yi Zhou
Fan Zhu
Li Liu
Ling Shao
AI4CE
176
275
0
27 Sep 2020
Encoding Robustness to Image Style via Adversarial Feature Perturbations
Encoding Robustness to Image Style via Adversarial Feature Perturbations
Manli Shu
Zuxuan Wu
Micah Goldblum
Tom Goldstein
AAMLOOD
75
19
0
18 Sep 2020
A Principle of Least Action for the Training of Neural Networks
A Principle of Least Action for the Training of Neural Networks
Skander Karkar
Ibrahhim Ayed
Emmanuel de Bézenac
Patrick Gallinari
AI4CE
69
10
0
17 Sep 2020
Review: Deep Learning in Electron Microscopy
Review: Deep Learning in Electron Microscopy
Jeffrey M. Ede
197
80
0
17 Sep 2020
XCM: An Explainable Convolutional Neural Network for Multivariate Time
  Series Classification
XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification
Kevin Fauvel
Tao R. Lin
Véronique Masson
Elisa Fromont
Alexandre Termier
BDLAI4TS
39
102
0
10 Sep 2020
Training Deep Neural Networks Without Batch Normalization
Training Deep Neural Networks Without Batch Normalization
D. Gaur
Joachim Folz
Andreas Dengel
ODL
54
10
0
18 Aug 2020
An Ensemble of Simple Convolutional Neural Network Models for MNIST
  Digit Recognition
An Ensemble of Simple Convolutional Neural Network Models for MNIST Digit Recognition
Sanghyeon An
Min Jun Lee
Sanglee Park
H. Yang
Jungmin So
87
79
0
12 Aug 2020
SimPose: Effectively Learning DensePose and Surface Normals of People
  from Simulated Data
SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data
Tyler Lixuan Zhu
Per Karlsson
C. Bregler
3DH
108
30
0
30 Jul 2020
A New Look at Ghost Normalization
A New Look at Ghost Normalization
Neofytos Dimitriou
Ognjen Arandjelovic
135
8
0
16 Jul 2020
Learning Representations that Support Extrapolation
Learning Representations that Support Extrapolation
Taylor Webb
Zachary Dulberg
Steven M. Frankland
A. Petrov
R. C. O'Reilly
Jonathan Cohen
90
51
0
09 Jul 2020
Testing match-3 video games with Deep Reinforcement Learning
Testing match-3 video games with Deep Reinforcement Learning
Nicholas Napolitano
15
3
0
30 Jun 2020
On the Generalization Benefit of Noise in Stochastic Gradient Descent
On the Generalization Benefit of Noise in Stochastic Gradient Descent
Samuel L. Smith
Erich Elsen
Soham De
MLT
62
100
0
26 Jun 2020
Diffusion-Weighted Magnetic Resonance Brain Images Generation with
  Generative Adversarial Networks and Variational Autoencoders: A Comparison
  Study
Diffusion-Weighted Magnetic Resonance Brain Images Generation with Generative Adversarial Networks and Variational Autoencoders: A Comparison Study
Alejandro Ungría Hirte
Moritz Platscher
T. Joyce
J. Heit
E. Tranvinh
C. Federau
MedImDiffM
24
6
0
24 Jun 2020
Spherical Perspective on Learning with Normalization Layers
Spherical Perspective on Learning with Normalization Layers
Simon Roburin
Yann de Mont-Marin
Andrei Bursuc
Renaud Marlet
P. Pérez
Mathieu Aubry
54
6
0
23 Jun 2020
DO-Conv: Depthwise Over-parameterized Convolutional Layer
DO-Conv: Depthwise Over-parameterized Convolutional Layer
Jinming Cao
Yangyan Li
Mingchao Sun
Ying-Cong Chen
Dani Lischinski
Daniel Cohen-Or
Baoquan Chen
Changhe Tu
OOD
101
173
0
22 Jun 2020
Towards an Adversarially Robust Normalization Approach
Towards an Adversarially Robust Normalization Approach
Muhammad Awais
Fahad Shamshad
Sung-Ho Bae
AAMLOOD
114
19
0
19 Jun 2020
New Interpretations of Normalization Methods in Deep Learning
New Interpretations of Normalization Methods in Deep Learning
Jiacheng Sun
Xiangyong Cao
Hanwen Liang
Weiran Huang
Zewei Chen
Zhenguo Li
68
35
0
16 Jun 2020
Optimization Theory for ReLU Neural Networks Trained with Normalization
  Layers
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers
Yonatan Dukler
Quanquan Gu
Guido Montúfar
83
30
0
11 Jun 2020
Finet: Using Fine-grained Batch Normalization to Train Light-weight
  Neural Networks
Finet: Using Fine-grained Batch Normalization to Train Light-weight Neural Networks
Chunjie Luo
Jianfeng Zhan
Lei Wang
Wanling Gao
137
1
0
14 May 2020
IsoBN: Fine-Tuning BERT with Isotropic Batch Normalization
IsoBN: Fine-Tuning BERT with Isotropic Batch Normalization
Wenxuan Zhou
Bill Yuchen Lin
Xiang Ren
100
25
0
02 May 2020
SIPA: A Simple Framework for Efficient Networks
SIPA: A Simple Framework for Efficient Networks
Gihun Lee
Sangmin Bae
Jaehoon Oh
Seyoung Yun
19
1
0
24 Apr 2020
Gradient Centralization: A New Optimization Technique for Deep Neural
  Networks
Gradient Centralization: A New Optimization Technique for Deep Neural Networks
Hongwei Yong
Jianqiang Huang
Xiansheng Hua
Lei Zhang
ODL
97
188
0
03 Apr 2020
Controllable Orthogonalization in Training DNNs
Controllable Orthogonalization in Training DNNs
Lei Huang
Li Liu
Fan Zhu
Diwen Wan
Zehuan Yuan
Bo Li
Ling Shao
87
44
0
02 Apr 2020
An Investigation into the Stochasticity of Batch Whitening
An Investigation into the Stochasticity of Batch Whitening
Lei Huang
Lei Zhao
Yi Zhou
Fan Zhu
Li Liu
Ling Shao
113
19
0
27 Mar 2020
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization
  Perspective
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
Qilong Wang
Li Zhang
Banggu Wu
Dongwei Ren
P. Li
W. Zuo
Q. Hu
75
21
0
25 Mar 2020
Geometric Approaches to Increase the Expressivity of Deep Neural
  Networks for MR Reconstruction
Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction
Eunju Cha
Gyutaek Oh
J. C. Ye
108
12
0
17 Mar 2020
Extended Batch Normalization
Extended Batch Normalization
Chunjie Luo
Jianfeng Zhan
Lei Wang
Wanling Gao
134
14
0
12 Mar 2020
Batch Normalization Provably Avoids Rank Collapse for Randomly
  Initialised Deep Networks
Batch Normalization Provably Avoids Rank Collapse for Randomly Initialised Deep Networks
Hadi Daneshmand
Jonas Köhler
Francis R. Bach
Thomas Hofmann
Aurelien Lucchi
OODODL
58
4
0
03 Mar 2020
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
115
143
0
29 Feb 2020
On Feature Normalization and Data Augmentation
On Feature Normalization and Data Augmentation
Boyi Li
Felix Wu
Ser-Nam Lim
Serge J. Belongie
Kilian Q. Weinberger
56
137
0
25 Feb 2020
Layer-wise Conditioning Analysis in Exploring the Learning Dynamics of
  DNNs
Layer-wise Conditioning Analysis in Exploring the Learning Dynamics of DNNs
Lei Huang
Jie Qin
Li Liu
Fan Zhu
Ling Shao
AI4CE
86
11
0
25 Feb 2020
Batch Normalization Biases Residual Blocks Towards the Identity Function
  in Deep Networks
Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks
Soham De
Samuel L. Smith
ODL
106
20
0
24 Feb 2020
The Break-Even Point on Optimization Trajectories of Deep Neural
  Networks
The Break-Even Point on Optimization Trajectories of Deep Neural Networks
Stanislaw Jastrzebski
Maciej Szymczak
Stanislav Fort
Devansh Arpit
Jacek Tabor
Kyunghyun Cho
Krzysztof J. Geras
88
164
0
21 Feb 2020
Regularizing activations in neural networks via distribution matching
  with the Wasserstein metric
Regularizing activations in neural networks via distribution matching with the Wasserstein metric
Taejong Joo
Donggu Kang
Byunghoon Kim
76
8
0
13 Feb 2020
How Does BN Increase Collapsed Neural Network Filters?
How Does BN Increase Collapsed Neural Network Filters?
Sheng Zhou
Xinjiang Wang
Ping Luo
Xue Jiang
Wenjie Li
Wei Zhang
45
1
0
30 Jan 2020
Evolution of Image Segmentation using Deep Convolutional Neural Network:
  A Survey
Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey
F. Sultana
Abu Sufian
P. Dutta
SSeg
141
258
0
13 Jan 2020
Empirical Studies on the Properties of Linear Regions in Deep Neural
  Networks
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks
Xiao Zhang
Dongrui Wu
58
38
0
04 Jan 2020
Optimization for deep learning: theory and algorithms
Optimization for deep learning: theory and algorithms
Ruoyu Sun
ODL
137
169
0
19 Dec 2019
Mean Shift Rejection: Training Deep Neural Networks Without Minibatch
  Statistics or Normalization
Mean Shift Rejection: Training Deep Neural Networks Without Minibatch Statistics or Normalization
B. Ruff
Taylor Beck
Joscha Bach
52
3
0
29 Nov 2019
Understanding and Improving Layer Normalization
Understanding and Improving Layer Normalization
Jingjing Xu
Xu Sun
Zhiyuan Zhang
Guangxiang Zhao
Junyang Lin
FAtt
122
360
0
16 Nov 2019
Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
Machine Learning Systems for Highly-Distributed and Rapidly-Growing Data
Kevin Hsieh
SyDaOOD
45
4
0
18 Oct 2019
Root Mean Square Layer Normalization
Root Mean Square Layer Normalization
Biao Zhang
Rico Sennrich
121
766
0
16 Oct 2019
An Exponential Learning Rate Schedule for Deep Learning
An Exponential Learning Rate Schedule for Deep Learning
Zhiyuan Li
Sanjeev Arora
74
219
0
16 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh
Amar Phanishayee
O. Mutlu
Phillip B. Gibbons
192
576
0
01 Oct 2019
U-Net Training with Instance-Layer Normalization
U-Net Training with Instance-Layer Normalization
Xiao-Yun Zhou
Peichao Li
Zhao-Yang Wang
Guang-Zhong Yang
50
9
0
21 Aug 2019
Neural Architecture Search by Estimation of Network Structure
  Distributions
Neural Architecture Search by Estimation of Network Structure Distributions
A. Muravev
Jenni Raitoharju
Moncef Gabbouj
OOD
20
1
0
19 Aug 2019
Towards Better Generalization: BP-SVRG in Training Deep Neural Networks
Towards Better Generalization: BP-SVRG in Training Deep Neural Networks
Hao Jin
Dachao Lin
Zhihua Zhang
ODL
42
2
0
18 Aug 2019
Instance Enhancement Batch Normalization: an Adaptive Regulator of Batch
  Noise
Instance Enhancement Batch Normalization: an Adaptive Regulator of Batch Noise
Senwei Liang
Zhongzhan Huang
Mingfu Liang
Haizhao Yang
102
59
0
12 Aug 2019
How Does Learning Rate Decay Help Modern Neural Networks?
How Does Learning Rate Decay Help Modern Neural Networks?
Kaichao You
Mingsheng Long
Jianmin Wang
Michael I. Jordan
68
4
0
05 Aug 2019
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