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Which Models have Perceptually-Aligned Gradients? An Explanation via
  Off-Manifold Robustness
v1v2 (latest)

Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness

30 May 2023
Suraj Srinivas
Sebastian Bordt
Hima Lakkaraju
    AAML
ArXiv (abs)PDFHTMLGithub (2★)

Papers citing "Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness"

17 / 17 papers shown
Title
Adversarially Pretrained Transformers may be Universally Robust In-Context Learners
Adversarially Pretrained Transformers may be Universally Robust In-Context Learners
Soichiro Kumano
Hiroshi Kera
Toshihiko Yamasaki
AAML
121
0
0
20 May 2025
Enhancing Diffusion-Based Image Synthesis with Robust Classifier
  Guidance
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance
Bahjat Kawar
Roy Ganz
Michael Elad
DiffM
65
39
0
18 Aug 2022
Which Explanation Should I Choose? A Function Approximation Perspective
  to Characterizing Post Hoc Explanations
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations
Tessa Han
Suraj Srinivas
Himabindu Lakkaraju
FAtt
103
88
0
02 Jun 2022
Elucidating the Design Space of Diffusion-Based Generative Models
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras
M. Aittala
Timo Aila
S. Laine
DiffM
222
2,033
0
01 Jun 2022
Towards Understanding the Generative Capability of Adversarially Robust
  Classifiers
Towards Understanding the Generative Capability of Adversarially Robust Classifiers
Yao Zhu
Jiacheng Ma
Jiacheng Sun
Zewei Chen
Rongxin Jiang
Zhenguo Li
AAML
69
24
0
20 Aug 2021
Have We Learned to Explain?: How Interpretability Methods Can Learn to
  Encode Predictions in their Interpretations
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
N. Jethani
Mukund Sudarshan
Yindalon Aphinyanagphongs
Rajesh Ranganath
FAtt
146
71
0
02 Mar 2021
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
339
704
0
19 Oct 2020
Fairwashing Explanations with Off-Manifold Detergent
Fairwashing Explanations with Off-Manifold Detergent
Christopher J. Anders
Plamen Pasliev
Ann-Kathrin Dombrowski
K. Müller
Pan Kessel
FAttFaML
63
97
0
20 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better?
Do Adversarially Robust ImageNet Models Transfer Better?
Hadi Salman
Andrew Ilyas
Logan Engstrom
Ashish Kapoor
Aleksander Madry
93
426
0
16 Jul 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
93
546
0
06 Dec 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
169
2,052
0
08 Feb 2019
Sanity Checks for Saliency Maps
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAttAAMLXAI
152
1,970
0
08 Oct 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
110
1,784
0
30 May 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
Eli Shechtman
Oliver Wang
EGVM
384
11,920
0
11 Jan 2018
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
319
12,138
0
19 Jun 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OODFAtt
193
6,024
0
04 Mar 2017
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
314
7,321
0
20 Dec 2013
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