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Threat Model-Agnostic Adversarial Defense using Diffusion Models

Threat Model-Agnostic Adversarial Defense using Diffusion Models

17 July 2022
Tsachi Blau
Roy Ganz
Bahjat Kawar
Alex M. Bronstein
Michael Elad
    AAML
    DiffM
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Papers citing "Threat Model-Agnostic Adversarial Defense using Diffusion Models"

38 / 38 papers shown
Title
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Francesco Croce
Sven Gowal
T. Brunner
Evan Shelhamer
Matthias Hein
A. Cemgil
TTA
AAML
206
69
0
28 Feb 2022
Denoising Diffusion Restoration Models
Denoising Diffusion Restoration Models
Bahjat Kawar
Michael Elad
Stefano Ermon
Jiaming Song
DiffM
262
823
0
27 Jan 2022
Unsolved Problems in ML Safety
Unsolved Problems in ML Safety
Dan Hendrycks
Nicholas Carlini
John Schulman
Jacob Steinhardt
236
286
0
28 Sep 2021
BIGRoC: Boosting Image Generation via a Robust Classifier
BIGRoC: Boosting Image Generation via a Robust Classifier
Roy Ganz
Michael Elad
44
10
0
08 Aug 2021
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential
  Equations
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng
Yutong He
Yang Song
Jiaming Song
Jiajun Wu
Jun-Yan Zhu
Stefano Ermon
DiffM
130
1,484
0
02 Aug 2021
The Dimpled Manifold Model of Adversarial Examples in Machine Learning
The Dimpled Manifold Model of Adversarial Examples in Machine Learning
A. Shamir
Odelia Melamed
Oriel BenShmuel
AAML
49
50
0
18 Jun 2021
Adversarial purification with Score-based generative models
Adversarial purification with Score-based generative models
Jongmin Yoon
Sung Ju Hwang
Juho Lee
DiffM
76
156
0
11 Jun 2021
SNIPS: Solving Noisy Inverse Problems Stochastically
SNIPS: Solving Noisy Inverse Problems Stochastically
Bahjat Kawar
Gregory Vaksman
Michael Elad
69
194
0
31 May 2021
High Perceptual Quality Image Denoising with a Posterior Sampling CGAN
High Perceptual Quality Image Denoising with a Posterior Sampling CGAN
Guy Ohayon
Theo Adrai
Gregory Vaksman
Michael Elad
P. Milanfar
GAN
102
37
0
06 Mar 2021
Improved Denoising Diffusion Probabilistic Models
Improved Denoising Diffusion Probabilistic Models
Alex Nichol
Prafulla Dhariwal
DiffM
295
3,648
0
18 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness
Recent Advances in Adversarial Training for Adversarial Robustness
Tao Bai
Jinqi Luo
Jun Zhao
Bihan Wen
Qian Wang
AAML
115
489
0
02 Feb 2021
Stochastic Image Denoising by Sampling from the Posterior Distribution
Stochastic Image Denoising by Sampling from the Posterior Distribution
Bahjat Kawar
Gregory Vaksman
Michael Elad
DiffM
60
63
0
23 Jan 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded
  Adversarial Examples
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal
Chongli Qin
J. Uesato
Timothy A. Mann
Pushmeet Kohli
AAML
47
331
0
07 Oct 2020
Denoising Diffusion Implicit Models
Denoising Diffusion Implicit Models
Jiaming Song
Chenlin Meng
Stefano Ermon
VLM
DiffM
213
7,294
0
06 Oct 2020
Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser
Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser
Zahra Kadkhodaie
Eero P. Simoncelli
77
85
0
27 Jul 2020
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Cassidy Laidlaw
Sahil Singla
Soheil Feizi
AAML
OOD
77
187
0
22 Jun 2020
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
507
17,888
0
19 Jun 2020
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of
  Energy-Based Models
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models
Mitch Hill
Jonathan Mitchell
Song-Chun Zhu
AAML
53
70
0
27 May 2020
On Adaptive Attacks to Adversarial Example Defenses
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramèr
Nicholas Carlini
Wieland Brendel
Aleksander Madry
AAML
253
831
0
19 Feb 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat
  it Like One
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
Mohammad Norouzi
Kevin Swersky
VLM
76
542
0
06 Dec 2019
Generative Modeling by Estimating Gradients of the Data Distribution
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
Stefano Ermon
SyDa
DiffM
213
3,870
0
12 Jul 2019
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Yuzhe Yang
Guo Zhang
Dina Katabi
Zhi Xu
AAML
85
170
0
28 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
OOD
VLM
158
3,423
0
28 Mar 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
130
2,028
0
08 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
127
2,542
0
24 Jan 2019
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
93
1,776
0
30 May 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using
  Generative Models
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei
Maya Kabkab
Rama Chellappa
AAML
GAN
82
1,176
0
17 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
197
3,180
0
01 Feb 2018
Mitigating Adversarial Effects Through Randomization
Mitigating Adversarial Effects Through Randomization
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Zhou Ren
Alan Yuille
AAML
99
1,054
0
06 Nov 2017
PixelDefend: Leveraging Generative Models to Understand and Defend
  against Adversarial Examples
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples
Yang Song
Taesup Kim
Sebastian Nowozin
Stefano Ermon
Nate Kushman
AAML
110
790
0
30 Oct 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
SILM
OOD
279
12,029
0
19 Jun 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural
  Networks
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Weilin Xu
David Evans
Yanjun Qi
AAML
72
1,260
0
04 Apr 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
461
3,138
0
04 Nov 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
239
8,548
0
16 Aug 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
322
7,971
0
23 May 2016
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
SyDa
DiffM
261
6,887
0
12 Mar 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
243
19,017
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
249
14,893
1
21 Dec 2013
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