Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1802.01421
Cited By
v1
v2
v3
v4 (latest)
First-order Adversarial Vulnerability of Neural Networks and Input Dimension
5 February 2018
Carl-Johann Simon-Gabriel
Yann Ollivier
Léon Bottou
Bernhard Schölkopf
David Lopez-Paz
AAML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"First-order Adversarial Vulnerability of Neural Networks and Input Dimension"
36 / 36 papers shown
A Learning Paradigm for Interpretable Gradients
Felipe Figueroa
Hanwei Zhang
R. Sicre
Yannis Avrithis
Stéphane Ayache
FAtt
261
0
0
23 Apr 2024
On Procedural Adversarial Noise Attack And Defense
Jun Yan
Xiaoyang Deng
Huilin Yin
Wancheng Ge
AAML
259
2
0
10 Aug 2021
Relating Adversarially Robust Generalization to Flat Minima
IEEE International Conference on Computer Vision (ICCV), 2021
David Stutz
Matthias Hein
Bernt Schiele
OOD
308
78
0
09 Apr 2021
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
Shihao Zhao
Jiabo He
Yisen Wang
James Bailey
Yue Liu
Yu-Gang Jiang
AAML
242
15
0
18 Jan 2021
On Connections between Regularizations for Improving DNN Robustness
Yiwen Guo
Long Chen
Yurong Chen
Changshui Zhang
AAML
142
14
0
04 Jul 2020
Orthogonal Deep Models As Defense Against Black-Box Attacks
M. Jalwana
Naveed Akhtar
Bennamoun
Lin Wang
AAML
222
11
0
26 Jun 2020
Towards an Adversarially Robust Normalization Approach
Muhammad Awais
Fahad Shamshad
Sung-Ho Bae
AAML
OOD
240
21
0
19 Jun 2020
Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning
Youngjoon Yu
Hong Joo Lee
Byeong Cheon Kim
Jung Uk Kim
Yong Man Ro
AAML
176
22
0
22 May 2020
A Framework for Enhancing Deep Neural Networks Against Adversarial Malware
Deqiang Li
Qianmu Li
Yanfang Ye
Shouhuai Xu
AAML
297
14
0
15 Apr 2020
Explaining Classifiers using Adversarial Perturbations on the Perceptual Ball
Andrew Elliott
Stephen Law
Chris Russell
AAML
307
4
0
19 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
International Conference on Learning Representations (ICLR), 2019
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
Mohammad Norouzi
Kevin Swersky
VLM
540
625
0
06 Dec 2019
Walking on the Edge: Fast, Low-Distortion Adversarial Examples
IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2019
Hanwei Zhang
Yannis Avrithis
Teddy Furon
Laurent Amsaleg
AAML
251
55
0
04 Dec 2019
Can Attention Masks Improve Adversarial Robustness?
Communications in Computer and Information Science (CCIS), 2019
Pratik Vaishnavi
Tianji Cong
Kevin Eykholt
A. Prakash
Amir Rahmati
AAML
309
13
0
27 Nov 2019
CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators
European Conference on Artificial Intelligence (ECAI), 2019
Julien Girard-Satabin
Guillaume Charpiat
Zakaria Chihani
Marc Schoenauer
OOD
AAML
116
3
0
25 Nov 2019
Not All Adversarial Examples Require a Complex Defense: Identifying Over-optimized Adversarial Examples with IQR-based Logit Thresholding
IEEE International Joint Conference on Neural Network (IJCNN), 2019
Utku Ozbulak
Arnout Van Messem
W. D. Neve
AAML
103
1
0
30 Jul 2019
Adversarial Training is a Form of Data-dependent Operator Norm Regularization
Kevin Roth
Yannic Kilcher
Thomas Hofmann
242
13
0
04 Jun 2019
Scaleable input gradient regularization for adversarial robustness
Machine Learning with Applications (MLWA), 2019
Chris Finlay
Adam M. Oberman
AAML
344
90
0
27 May 2019
On the Connection Between Adversarial Robustness and Saliency Map Interpretability
International Conference on Machine Learning (ICML), 2019
Christian Etmann
Sebastian Lunz
Peter Maass
Carola-Bibiane Schönlieb
AAML
FAtt
226
174
0
10 May 2019
Adversarial Defense Framework for Graph Neural Network
Shen Wang
Zhengzhang Chen
Jingchao Ni
Xiao Yu
Zhichun Li
Haifeng Chen
Philip S. Yu
AAML
GNN
199
30
0
09 May 2019
Batch Normalization is a Cause of Adversarial Vulnerability
A. Galloway
A. Golubeva
T. Tanay
M. Moussa
Graham W. Taylor
ODL
AAML
269
84
0
06 May 2019
L 1-norm double backpropagation adversarial defense
The European Symposium on Artificial Neural Networks (ESANN), 2019
Ismaïla Seck
Gaëlle Loosli
S. Canu
GAN
AAML
178
4
0
05 Mar 2019
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors
Ke Sun
Zhanxing Zhu
Zhouchen Lin
AAML
179
19
0
28 Feb 2019
Theoretical evidence for adversarial robustness through randomization
Rafael Pinot
Laurent Meunier
Alexandre Araujo
H. Kashima
Florian Yger
Cédric Gouy-Pailler
Jamal Atif
AAML
327
90
0
04 Feb 2019
Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge
Deqiang Li
Qianmu Li
Yanfang Ye
Shouhuai Xu
AAML
322
17
0
19 Dec 2018
Adversarial Attacks, Regression, and Numerical Stability Regularization
A. Nguyen
Edward Raff
AAML
175
33
0
07 Dec 2018
Disentangling Adversarial Robustness and Generalization
David Stutz
Matthias Hein
Bernt Schiele
AAML
OOD
752
311
0
03 Dec 2018
Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding
Yao Li
Martin Renqiang Min
Wenchao Yu
Cho-Jui Hsieh
T. C. Lee
E. Kruus
OT
217
7
0
19 Nov 2018
Sorting out Lipschitz function approximation
Cem Anil
James Lucas
Roger C. Grosse
388
364
0
13 Nov 2018
A Kernel Perspective for Regularizing Deep Neural Networks
A. Bietti
Grégoire Mialon
Dexiong Chen
Julien Mairal
279
15
0
30 Sep 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks
Ambra Demontis
Marco Melis
Maura Pintor
Matthew Jagielski
Battista Biggio
Alina Oprea
Cristina Nita-Rotaru
Fabio Roli
SILM
AAML
371
11
0
08 Sep 2018
Are adversarial examples inevitable?
Ali Shafahi
Wenjie Huang
Christoph Studer
Soheil Feizi
Tom Goldstein
SILM
486
293
0
06 Sep 2018
Mitigation of Adversarial Attacks through Embedded Feature Selection
Ziyi Bao
Luis Muñoz-González
Emil C. Lupu
AAML
154
1
0
16 Aug 2018
Simultaneous Adversarial Training - Learn from Others Mistakes
IEEE International Conference on Automatic Face & Gesture Recognition (FG), 2018
Zukang Liao
AAML
GAN
203
4
0
21 Jul 2018
Adversarially Robust Training through Structured Gradient Regularization
Kevin Roth
Aurelien Lucchi
Sebastian Nowozin
Thomas Hofmann
173
24
0
22 May 2018
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization
Daniel Jakubovitz
Raja Giryes
AAML
468
228
0
23 Mar 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Battista Biggio
Fabio Roli
AAML
391
1,567
0
08 Dec 2017
1
Page 1 of 1
