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Adversarial Examples Are Not Bugs, They Are Features

Adversarial Examples Are Not Bugs, They Are Features

6 May 2019
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
A. Madry
    SILM
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Papers citing "Adversarial Examples Are Not Bugs, They Are Features"

50 / 297 papers shown
Title
An Overview of Laser Injection against Embedded Neural Network Models
An Overview of Laser Injection against Embedded Neural Network Models
Mathieu Dumont
Pierre-Alain Moëllic
R. Viera
J. Dutertre
Rémi Bernhard
AAML
22
9
0
04 May 2021
Impact of Spatial Frequency Based Constraints on Adversarial Robustness
Impact of Spatial Frequency Based Constraints on Adversarial Robustness
Rémi Bernhard
Pierre-Alain Moëllic
Martial Mermillod
Yannick Bourrier
Romain Cohendet
M. Solinas
M. Reyboz
AAML
19
16
0
26 Apr 2021
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics
J. Hayase
Weihao Kong
Raghav Somani
Sewoong Oh
AAML
19
149
0
22 Apr 2021
Understanding and Avoiding AI Failures: A Practical Guide
Understanding and Avoiding AI Failures: A Practical Guide
R. M. Williams
Roman V. Yampolskiy
19
23
0
22 Apr 2021
Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in
  Visual Question Answering
Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering
Corentin Dancette
Rémi Cadène
Damien Teney
Matthieu Cord
CML
28
75
0
07 Apr 2021
Universal Adversarial Training with Class-Wise Perturbations
Universal Adversarial Training with Class-Wise Perturbations
Philipp Benz
Chaoning Zhang
Adil Karjauv
In So Kweon
AAML
10
26
0
07 Apr 2021
On the Adversarial Robustness of Vision Transformers
On the Adversarial Robustness of Vision Transformers
Rulin Shao
Zhouxing Shi
Jinfeng Yi
Pin-Yu Chen
Cho-Jui Hsieh
ViT
30
137
0
29 Mar 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for
  Enhanced Adversarial Robustness
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
Yi Cai
Xuefei Ning
Huazhong Yang
Yu Wang
AAML
25
4
0
27 Mar 2021
Characterizing and Improving the Robustness of Self-Supervised Learning
  through Background Augmentations
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations
Chaitanya K. Ryali
D. Schwab
Ari S. Morcos
SSL
32
9
0
23 Mar 2021
Adversarially Optimized Mixup for Robust Classification
Adversarially Optimized Mixup for Robust Classification
Jason Bunk
Srinjoy Chattopadhyay
B. S. Manjunath
S. Chandrasekaran
AAML
24
8
0
22 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal
Robust Models Are More Interpretable Because Attributions Look Normal
Zifan Wang
Matt Fredrikson
Anupam Datta
OOD
FAtt
28
25
0
20 Mar 2021
Explainable Adversarial Attacks in Deep Neural Networks Using Activation
  Profiles
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles
G. Cantareira
R. Mello
F. Paulovich
AAML
16
9
0
18 Mar 2021
Bio-inspired Robustness: A Review
Bio-inspired Robustness: A Review
Harshitha Machiraju
Oh-hyeon Choung
P. Frossard
Michael H. Herzog
AAML
30
1
0
16 Mar 2021
Adversarial Training is Not Ready for Robot Learning
Adversarial Training is Not Ready for Robot Learning
Mathias Lechner
Ramin Hasani
Radu Grosu
Daniela Rus
T. Henzinger
AAML
30
34
0
15 Mar 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness
A Unified Game-Theoretic Interpretation of Adversarial Robustness
Jie Ren
Die Zhang
Yisen Wang
Lu Chen
Zhanpeng Zhou
...
Xu Cheng
Xin Eric Wang
Meng Zhou
Jie Shi
Quanshi Zhang
AAML
69
22
0
12 Mar 2021
Maximum Entropy RL (Provably) Solves Some Robust RL Problems
Maximum Entropy RL (Provably) Solves Some Robust RL Problems
Benjamin Eysenbach
Sergey Levine
OOD
24
174
0
10 Mar 2021
Detecting Spurious Correlations with Sanity Tests for Artificial
  Intelligence Guided Radiology Systems
Detecting Spurious Correlations with Sanity Tests for Artificial Intelligence Guided Radiology Systems
U. Mahmood
Robik Shrestha
D. Bates
L. Mannelli
G. Corrias
Y. Erdi
Christopher Kanan
16
16
0
04 Mar 2021
A Survey On Universal Adversarial Attack
A Survey On Universal Adversarial Attack
Chaoning Zhang
Philipp Benz
Chenguo Lin
Adil Karjauv
Jing Wu
In So Kweon
AAML
23
90
0
02 Mar 2021
Dual Attention Suppression Attack: Generate Adversarial Camouflage in
  Physical World
Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
Jiakai Wang
Aishan Liu
Zixin Yin
Shunchang Liu
Shiyu Tang
Xianglong Liu
AAML
138
194
0
01 Mar 2021
Counterfactual Zero-Shot and Open-Set Visual Recognition
Counterfactual Zero-Shot and Open-Set Visual Recognition
Zhongqi Yue
Tan Wang
Hanwang Zhang
Qianru Sun
Xiansheng Hua
BDL
158
192
0
01 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Alec Radford
Jong Wook Kim
Chris Hallacy
Aditya A. Ramesh
Gabriel Goh
...
Amanda Askell
Pamela Mishkin
Jack Clark
Gretchen Krueger
Ilya Sutskever
CLIP
VLM
103
27,682
0
26 Feb 2021
Understanding Robustness in Teacher-Student Setting: A New Perspective
Understanding Robustness in Teacher-Student Setting: A New Perspective
Zhuolin Yang
Zhaoxi Chen
Tiffany Cai
Xinyun Chen
Bo-wen Li
Yuandong Tian
AAML
27
2
0
25 Feb 2021
Do Input Gradients Highlight Discriminative Features?
Do Input Gradients Highlight Discriminative Features?
Harshay Shah
Prateek Jain
Praneeth Netrapalli
AAML
FAtt
21
57
0
25 Feb 2021
Adversarial Robustness with Non-uniform Perturbations
Adversarial Robustness with Non-uniform Perturbations
Ece Naz Erdemir
Jeffrey Bickford
Luca Melis
Sergul Aydore
AAML
16
26
0
24 Feb 2021
Dompteur: Taming Audio Adversarial Examples
Dompteur: Taming Audio Adversarial Examples
Thorsten Eisenhofer
Lea Schonherr
Joel Frank
Lars Speckemeier
D. Kolossa
Thorsten Holz
AAML
28
24
0
10 Feb 2021
Robusta: Robust AutoML for Feature Selection via Reinforcement Learning
Robusta: Robust AutoML for Feature Selection via Reinforcement Learning
Xiaoyang Sean Wang
Bo-wen Li
Yibo Zhang
B. Kailkhura
K. Nahrstedt
13
3
0
15 Jan 2021
Unlearnable Examples: Making Personal Data Unexploitable
Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang
Xingjun Ma
S. Erfani
James Bailey
Yisen Wang
MIACV
139
190
0
13 Jan 2021
Deep Feature Space Trojan Attack of Neural Networks by Controlled
  Detoxification
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification
Shuyang Cheng
Yingqi Liu
Shiqing Ma
X. Zhang
AAML
20
154
0
21 Dec 2020
On Success and Simplicity: A Second Look at Transferable Targeted
  Attacks
On Success and Simplicity: A Second Look at Transferable Targeted Attacks
Zhengyu Zhao
Zhuoran Liu
Martha Larson
AAML
24
121
0
21 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep
  image classifiers
On the human-recognizability phenomenon of adversarially trained deep image classifiers
Jonathan W. Helland
Nathan M. VanHoudnos
AAML
22
4
0
18 Dec 2020
Applying Deutsch's concept of good explanations to artificial
  intelligence and neuroscience -- an initial exploration
Applying Deutsch's concept of good explanations to artificial intelligence and neuroscience -- an initial exploration
Daniel C. Elton
13
4
0
16 Dec 2020
Achieving Adversarial Robustness Requires An Active Teacher
Achieving Adversarial Robustness Requires An Active Teacher
Chao Ma
Lexing Ying
19
1
0
14 Dec 2020
Learning Energy-Based Models With Adversarial Training
Learning Energy-Based Models With Adversarial Training
Xuwang Yin
Shiying Li
Gustavo K. Rohde
AAML
DiffM
30
9
0
11 Dec 2020
Provable Defense against Privacy Leakage in Federated Learning from
  Representation Perspective
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
Jingwei Sun
Ang Li
Binghui Wang
Huanrui Yang
Hai Li
Yiran Chen
FedML
19
162
0
08 Dec 2020
On 1/n neural representation and robustness
On 1/n neural representation and robustness
Josue Nassar
Piotr A. Sokól
SueYeon Chung
K. Harris
Il Memming Park
AAML
OOD
18
23
0
08 Dec 2020
Truly shift-invariant convolutional neural networks
Truly shift-invariant convolutional neural networks
Anadi Chaman
Ivan Dokmanić
23
68
0
28 Nov 2020
Adversarial Classification: Necessary conditions and geometric flows
Adversarial Classification: Necessary conditions and geometric flows
Nicolas García Trillos
Ryan W. Murray
AAML
17
19
0
21 Nov 2020
Certified Monotonic Neural Networks
Certified Monotonic Neural Networks
Xingchao Liu
Xing Han
Na Zhang
Qiang Liu
21
78
0
20 Nov 2020
Gradient Starvation: A Learning Proclivity in Neural Networks
Gradient Starvation: A Learning Proclivity in Neural Networks
Mohammad Pezeshki
Sekouba Kaba
Yoshua Bengio
Aaron Courville
Doina Precup
Guillaume Lajoie
MLT
45
257
0
18 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine
  Learning
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander DÁmour
Katherine A. Heller
D. Moldovan
Ben Adlam
B. Alipanahi
...
Kellie Webster
Steve Yadlowsky
T. Yun
Xiaohua Zhai
D. Sculley
OffRL
48
669
0
06 Nov 2020
Learning Causal Semantic Representation for Out-of-Distribution
  Prediction
Learning Causal Semantic Representation for Out-of-Distribution Prediction
Chang-Shu Liu
Xinwei Sun
Jindong Wang
Haoyue Tang
Tao Li
Tao Qin
Wei Chen
Tie-Yan Liu
CML
OODD
OOD
29
104
0
03 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural
  Networks
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks
Tao Bai
Jinqi Luo
Jun Zhao
AAML
43
8
0
03 Nov 2020
Context Dependent Semantic Parsing: A Survey
Context Dependent Semantic Parsing: A Survey
Zhuang Li
Lizhen Qu
Gholamreza Haffari
13
19
0
02 Nov 2020
Adversarial Robust Training of Deep Learning MRI Reconstruction Models
Adversarial Robust Training of Deep Learning MRI Reconstruction Models
Francesco Calivá
Kaiyang Cheng
Rutwik Shah
V. Pedoia
OOD
AAML
MedIm
19
10
0
30 Oct 2020
Exemplary Natural Images Explain CNN Activations Better than
  State-of-the-Art Feature Visualization
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization
Judy Borowski
Roland S. Zimmermann
Judith Schepers
Robert Geirhos
Thomas S. A. Wallis
Matthias Bethge
Wieland Brendel
FAtt
36
7
0
23 Oct 2020
Data-driven Identification of 2D Partial Differential Equations using
  extracted physical features
Data-driven Identification of 2D Partial Differential Equations using extracted physical features
Kazem Meidani
A. Farimani
21
17
0
20 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep
  Learning through Adversarial Robustness
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness
Guillermo Ortiz-Jiménez
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
29
48
0
19 Oct 2020
GreedyFool: Multi-Factor Imperceptibility and Its Application to
  Designing a Black-box Adversarial Attack
GreedyFool: Multi-Factor Imperceptibility and Its Application to Designing a Black-box Adversarial Attack
Hui Liu
Bo Zhao
Minzhi Ji
Peng Liu
AAML
27
6
0
14 Oct 2020
A Unified Approach to Interpreting and Boosting Adversarial
  Transferability
A Unified Approach to Interpreting and Boosting Adversarial Transferability
Xin Eric Wang
Jie Ren
Shuyu Lin
Xiangming Zhu
Yisen Wang
Quanshi Zhang
AAML
23
94
0
08 Oct 2020
Generating End-to-End Adversarial Examples for Malware Classifiers Using
  Explainability
Generating End-to-End Adversarial Examples for Malware Classifiers Using Explainability
Ishai Rosenberg
Shai Meir
J. Berrebi
I. Gordon
Guillaume Sicard
Eli David
AAML
SILM
9
25
0
28 Sep 2020
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