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Weight and Gradient Centralization in Deep Neural Networks

Weight and Gradient Centralization in Deep Neural Networks

2 October 2020
Wolfgang Fuhl
Enkelejda Kasneci
    ODL
ArXivPDFHTML

Papers citing "Weight and Gradient Centralization in Deep Neural Networks"

26 / 26 papers shown
Title
Explainable Online Validation of Machine Learning Models for Practical
  Applications
Explainable Online Validation of Machine Learning Models for Practical Applications
Wolfgang Fuhl
Yao Rong
T. Motz
Michael Scheidt
Andreas Hartel
Andreas Koch
Enkelejda Kasneci
FaML
144
14
0
02 Oct 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
66
186
0
03 Apr 2020
Fully Convolutional Neural Networks for Raw Eye Tracking Data
  Segmentation, Generation, and Reconstruction
Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction
Wolfgang Fuhl
Yao Rong
Enkelejda Kasneci
49
38
0
17 Feb 2020
Training Decision Trees as Replacement for Convolution Layers
Training Decision Trees as Replacement for Convolution Layers
Wolfgang Fuhl
Gjergji Kasneci
W. Rosenstiel
Enkelejda Kasneci
43
18
0
24 May 2019
Micro-Batch Training with Batch-Channel Normalization and Weight
  Standardization
Micro-Batch Training with Batch-Channel Normalization and Weight Standardization
Siyuan Qiao
Huiyu Wang
Chenxi Liu
Wei Shen
Alan Yuille
MQ
95
144
0
25 Mar 2019
Learning to Validate the Quality of Detected Landmarks
Learning to Validate the Quality of Detected Landmarks
Wolfgang Fuhl
Enkelejda Kasneci
68
19
0
29 Jan 2019
Eye movement velocity and gaze data generator for evaluation, robustness
  testing and assess of eye tracking software and visualization tools
Eye movement velocity and gaze data generator for evaluation, robustness testing and assess of eye tracking software and visualization tools
Wolfgang Fuhl
Enkelejda Kasneci
41
21
0
27 Aug 2018
How Does Batch Normalization Help Optimization?
How Does Batch Normalization Help Optimization?
Shibani Santurkar
Dimitris Tsipras
Andrew Ilyas
Aleksander Madry
ODL
97
1,542
0
29 May 2018
Eye movement simulation and detector creation to reduce laborious
  parameter adjustments
Eye movement simulation and detector creation to reduce laborious parameter adjustments
Wolfgang Fuhl
Thiago Santini
Thomas C. Kübler
N. Castner
W. Rosenstiel
Enkelejda Kasneci
30
22
0
28 Mar 2018
Group Normalization
Group Normalization
Yuxin Wu
Kaiming He
228
3,660
0
22 Mar 2018
Fast camera focus estimation for gaze-based focus control
Fast camera focus estimation for gaze-based focus control
Wolfgang Fuhl
Thiago Santini
Enkelejda Kasneci
62
21
0
09 Nov 2017
Riemannian approach to batch normalization
Riemannian approach to batch normalization
Minhyung Cho
Jaehyung Lee
55
94
0
27 Sep 2017
CNN-Based Projected Gradient Descent for Consistent Image Reconstruction
CNN-Based Projected Gradient Descent for Consistent Image Reconstruction
Harshit Gupta
Kyong Hwan Jin
H. Nguyen
Michael T. McCann
M. Unser
3DV
107
366
0
06 Sep 2017
Arbitrary Style Transfer in Real-time with Adaptive Instance
  Normalization
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
Xun Huang
Serge J. Belongie
OOD
179
4,364
0
20 Mar 2017
Instance Normalization: The Missing Ingredient for Fast Stylization
Instance Normalization: The Missing Ingredient for Fast Stylization
Dmitry Ulyanov
Andrea Vedaldi
Victor Lempitsky
OOD
174
3,708
0
27 Jul 2016
Layer Normalization
Layer Normalization
Jimmy Lei Ba
J. Kiros
Geoffrey E. Hinton
413
10,494
0
21 Jul 2016
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOS
SSeg
741
37,862
0
20 May 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training
  of Deep Neural Networks
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Tim Salimans
Diederik P. Kingma
ODL
194
1,942
0
25 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Variational Dropout and the Local Reparameterization Trick
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma
Tim Salimans
Max Welling
BDL
223
1,514
0
08 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
1.8K
77,196
0
18 May 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
463
43,305
0
11 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
323
18,625
0
06 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,115
0
22 Dec 2014
Generative Adversarial Networks
Generative Adversarial Networks
Ian Goodfellow
Jean Pouget-Abadie
M. Berk Mirza
Bing Xu
David Warde-Farley
Sherjil Ozair
Aaron Courville
Yoshua Bengio
GAN
139
2,193
0
10 Jun 2014
On the difficulty of training Recurrent Neural Networks
On the difficulty of training Recurrent Neural Networks
Razvan Pascanu
Tomas Mikolov
Yoshua Bengio
ODL
190
5,346
0
21 Nov 2012
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