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Achieving Generalizable Robustness of Deep Neural Networks by Stability
  Training
v1v2 (latest)

Achieving Generalizable Robustness of Deep Neural Networks by Stability Training

3 June 2019
Jan Laermann
Wojciech Samek
Nils Strodthoff
    OOD
ArXiv (abs)PDFHTML

Papers citing "Achieving Generalizable Robustness of Deep Neural Networks by Stability Training"

19 / 19 papers shown
Title
Does Data Augmentation Lead to Positive Margin?
Does Data Augmentation Lead to Positive Margin?
Shashank Rajput
Zhili Feng
Zachary B. Charles
Po-Ling Loh
Dimitris Papailiopoulos
64
38
0
08 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot
Nicholas Carlini
Ian Goodfellow
Nicolas Papernot
Avital Oliver
Colin Raffel
145
3,033
0
06 May 2019
Learning Optimal Data Augmentation Policies via Bayesian Optimization
  for Image Classification Tasks
Learning Optimal Data Augmentation Policies via Bayesian Optimization for Image Classification Tasks
Chunxu Zhang
Jiaxu Cui
Bo Yang
56
3
0
06 May 2019
Interpolation Consistency Training for Semi-Supervised Learning
Interpolation Consistency Training for Semi-Supervised Learning
Vikas Verma
Kenji Kawaguchi
Alex Lamb
Arno Solin
Arno Solin
Yoshua Bengio
David Lopez-Paz
107
770
0
09 Mar 2019
On Evaluating Adversarial Robustness
On Evaluating Adversarial Robustness
Nicholas Carlini
Anish Athalye
Nicolas Papernot
Wieland Brendel
Jonas Rauber
Dimitris Tsipras
Ian Goodfellow
Aleksander Madry
Alexey Kurakin
ELMAAML
89
901
0
18 Feb 2019
AutoAugment: Learning Augmentation Policies from Data
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
133
1,774
0
24 May 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
282
9,797
0
25 Oct 2017
Improving Deep Learning using Generic Data Augmentation
Improving Deep Learning using Generic Data Augmentation
Luke Taylor
G. Nitschke
54
383
0
20 Aug 2017
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
291
2,266
0
24 Jun 2017
Virtual Adversarial Training: A Regularization Method for Supervised and
  Semi-Supervised Learning
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato
S. Maeda
Masanori Koyama
S. Ishii
GAN
148
2,738
0
13 Apr 2017
Temporal Ensembling for Semi-Supervised Learning
Temporal Ensembling for Semi-Supervised Learning
S. Laine
Timo Aila
UQCV
185
2,566
0
07 Oct 2016
Regularization With Stochastic Transformations and Perturbations for
  Deep Semi-Supervised Learning
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
Mehdi S. M. Sajjadi
Mehran Javanmardi
Tolga Tasdizen
BDL
85
1,115
0
14 Jun 2016
Improving the Robustness of Deep Neural Networks via Stability Training
Improving the Robustness of Deep Neural Networks via Stability Training
Stephan Zheng
Yang Song
Thomas Leung
Ian Goodfellow
OOD
50
639
0
15 Apr 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,322
0
10 Dec 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
43,328
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
326
18,647
0
06 Feb 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
280
19,107
0
20 Dec 2014
Learning with Pseudo-Ensembles
Learning with Pseudo-Ensembles
Philip Bachman
O. Alsharif
Doina Precup
89
601
0
16 Dec 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
277
14,961
1
21 Dec 2013
1