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CEB Improves Model Robustness

CEB Improves Model Robustness

13 February 2020
Ian S. Fischer
Alexander A. Alemi
    AAML
ArXiv (abs)PDFHTML

Papers citing "CEB Improves Model Robustness"

30 / 30 papers shown
Title
The Conditional Entropy Bottleneck
The Conditional Entropy Bottleneck
Ian S. Fischer
OOD
105
121
0
13 Feb 2020
Extracting robust and accurate features via a robust information
  bottleneck
Extracting robust and accurate features via a robust information bottleneck
Ankit Pensia
Varun Jog
Po-Ling Loh
AAML
45
20
0
15 Oct 2019
Learnability for the Information Bottleneck
Learnability for the Information Bottleneck
Tailin Wu
Ian S. Fischer
Isaac L. Chuang
Max Tegmark
51
42
0
17 Jul 2019
Natural Adversarial Examples
Natural Adversarial Examples
Dan Hendrycks
Kevin Zhao
Steven Basart
Jacob Steinhardt
Basel Alomair
OODD
223
1,482
0
16 Jul 2019
A Fourier Perspective on Model Robustness in Computer Vision
A Fourier Perspective on Model Robustness in Computer Vision
Dong Yin
Raphael Gontijo-Lopes
Jonathon Shlens
E. D. Cubuk
Justin Gilmer
OOD
81
502
0
21 Jun 2019
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian
  Augmentation
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation
Raphael Gontijo-Lopes
Dong Yin
Ben Poole
Justin Gilmer
E. D. Cubuk
AAML
142
205
0
06 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive
  Uncertainty Under Dataset Shift
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
UQCV
183
1,702
0
06 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
SILM
93
1,844
0
06 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and
  Perturbations
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks
Thomas G. Dietterich
OODVLM
191
3,452
0
28 Mar 2019
Feature Denoising for Improving Adversarial Robustness
Feature Denoising for Improving Adversarial Robustness
Cihang Xie
Yuxin Wu
Laurens van der Maaten
Alan Yuille
Kaiming He
113
912
0
09 Dec 2018
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Benjamin Recht
Rebecca Roelofs
Ludwig Schmidt
Vaishaal Shankar
OODFedMLELM
171
414
0
01 Jun 2018
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
108
1,782
0
30 May 2018
AutoAugment: Learning Augmentation Policies from Data
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
135
1,775
0
24 May 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
243
3,194
0
01 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
285
8,920
0
25 Aug 2017
Robust Physical-World Attacks on Deep Learning Models
Robust Physical-World Attacks on Deep Learning Models
Kevin Eykholt
Ivan Evtimov
Earlence Fernandes
Yue Liu
Amir Rahmati
Chaowei Xiao
Atul Prakash
Tadayoshi Kohno
Basel Alomair
AAML
76
595
0
27 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILMOOD
317
12,131
0
19 Jun 2017
Emergence of Invariance and Disentanglement in Deep Representations
Emergence of Invariance and Disentanglement in Deep Representations
Alessandro Achille
Stefano Soatto
OODDRL
96
477
0
05 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection
  Methods
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods
Nicholas Carlini
D. Wagner
AAML
131
1,864
0
20 May 2017
Adversarial Transformation Networks: Learning to Generate Adversarial
  Examples
Adversarial Transformation Networks: Learning to Generate Adversarial Examples
S. Baluja
Ian S. Fischer
GAN
79
286
0
28 Mar 2017
Deep Variational Information Bottleneck
Deep Variational Information Bottleneck
Alexander A. Alemi
Ian S. Fischer
Joshua V. Dillon
Kevin Patrick Murphy
128
1,728
0
01 Dec 2016
Information Dropout: Learning Optimal Representations Through Noisy
  Computation
Information Dropout: Learning Optimal Representations Through Noisy Computation
Alessandro Achille
Stefano Soatto
OODDRLSSL
65
405
0
04 Nov 2016
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
472
3,148
0
04 Nov 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
282
8,583
0
16 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
545
5,910
0
08 Jul 2016
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
154
4,905
0
14 Nov 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
465
43,341
0
11 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,312
0
22 Dec 2014
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,121
0
20 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
282
14,963
1
21 Dec 2013
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