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Adversarial examples in the physical world
v1v2v3v4 (latest)

Adversarial examples in the physical world

8 July 2016
Alexey Kurakin
Ian Goodfellow
Samy Bengio
    SILMAAML
ArXiv (abs)PDFHTML

Papers citing "Adversarial examples in the physical world"

19 / 2,769 papers shown
Title
Adversarial examples for generative models
Adversarial examples for generative models
Jernej Kos
Ian S. Fischer
Basel Alomair
GAN
95
274
0
22 Feb 2017
On Detecting Adversarial Perturbations
On Detecting Adversarial Perturbations
J. H. Metzen
Tim Genewein
Volker Fischer
Bastian Bischoff
AAML
125
952
0
14 Feb 2017
Adversarial Attacks on Neural Network Policies
Adversarial Attacks on Neural Network Policies
Sandy Huang
Nicolas Papernot
Ian Goodfellow
Yan Duan
Pieter Abbeel
MLAUAAML
123
840
0
08 Feb 2017
Dense Associative Memory is Robust to Adversarial Inputs
Dense Associative Memory is Robust to Adversarial Inputs
Dmitry Krotov
J. Hopfield
AAML
84
113
0
04 Jan 2017
Adversarial Examples Detection in Deep Networks with Convolutional
  Filter Statistics
Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics
Xin Li
Fuxin Li
GANAAML
145
366
0
22 Dec 2016
Simple Black-Box Adversarial Perturbations for Deep Networks
Simple Black-Box Adversarial Perturbations for Deep Networks
Nina Narodytska
S. Kasiviswanathan
AAML
84
239
0
19 Dec 2016
Deep Variational Information Bottleneck
Deep Variational Information Bottleneck
Alexander A. Alemi
Ian S. Fischer
Joshua V. Dillon
Kevin Patrick Murphy
203
1,735
0
01 Dec 2016
Towards the Science of Security and Privacy in Machine Learning
Towards the Science of Security and Privacy in Machine Learning
Nicolas Papernot
Patrick McDaniel
Arunesh Sinha
Michael P. Wellman
AAML
99
474
0
11 Nov 2016
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
491
3,152
0
04 Nov 2016
Towards Lifelong Self-Supervision: A Deep Learning Direction for
  Robotics
Towards Lifelong Self-Supervision: A Deep Learning Direction for Robotics
J. M. Wong
79
11
0
01 Nov 2016
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
Marta Kwiatkowska
Sen Wang
Min Wu
AAML
290
945
0
21 Oct 2016
Are Accuracy and Robustness Correlated?
Are Accuracy and Robustness Correlated?
Andras Rozsa
Manuel Günther
Terrance E. Boult
AAML
78
61
0
14 Oct 2016
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library
Nicolas Papernot
Fartash Faghri
Nicholas Carlini
Ian Goodfellow
Reuben Feinman
...
David Berthelot
P. Hendricks
Jonas Rauber
Rujun Long
Patrick McDaniel
AAML
98
516
0
03 Oct 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
290
8,604
0
16 Aug 2016
Spoofing 2D Face Detection: Machines See People Who Aren't There
Spoofing 2D Face Detection: Machines See People Who Aren't There
Michael McCoyd
David Wagner
CVBM
70
4
0
06 Aug 2016
A study of the effect of JPG compression on adversarial images
A study of the effect of JPG compression on adversarial images
Gintare Karolina Dziugaite
Zoubin Ghahramani
Daniel M. Roy
AAML
96
536
0
02 Aug 2016
Early Methods for Detecting Adversarial Images
Early Methods for Detecting Adversarial Images
Dan Hendrycks
Kevin Gimpel
AAML
105
236
0
01 Aug 2016
Unsupervised Learning from Continuous Video in a Scalable Predictive
  Recurrent Network
Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network
Filip Piekniewski
Patryk A. Laurent
Csaba Petre
Micah Richert
Dimitry Fisher
Todd Hylton
56
17
0
22 Jul 2016
Practical Black-Box Attacks against Machine Learning
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAUAAML
100
3,690
0
08 Feb 2016
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