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Efficient and Transferable Adversarial Examples from Bayesian Neural
  Networks
v1v2v3v4 (latest)

Efficient and Transferable Adversarial Examples from Bayesian Neural Networks

10 November 2020
Martin Gubri
Maxime Cordy
Mike Papadakis
Yves Le Traon
Koushik Sen
    AAML
ArXiv (abs)PDFHTML

Papers citing "Efficient and Transferable Adversarial Examples from Bayesian Neural Networks"

7 / 7 papers shown
Understanding Model Ensemble in Transferable Adversarial Attack
Understanding Model Ensemble in Transferable Adversarial Attack
Wei Yao
Zeliang Zhang
Huayi Tang
Yong Liu
569
4
0
09 Oct 2024
A Curious Case of Remarkable Resilience to Gradient Attacks via Fully Convolutional and Differentiable Front End with a Skip Connection
A Curious Case of Remarkable Resilience to Gradient Attacks via Fully Convolutional and Differentiable Front End with a Skip Connection
Leonid Boytsov
Ameya Joshi
Filipe Condessa
AAML
302
0
0
26 Feb 2024
Improving Transferability of Adversarial Examples via Bayesian Attacks
Improving Transferability of Adversarial Examples via Bayesian Attacks
Qizhang Li
Yiwen Guo
Xiaochen Yang
W. Zuo
Hao Chen
AAMLBDL
350
2
0
21 Jul 2023
Why Does Little Robustness Help? Understanding and Improving Adversarial
  Transferability from Surrogate Training
Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate TrainingIEEE Symposium on Security and Privacy (IEEE S&P), 2023
Yechao Zhang
Shengshan Hu
Leo Yu Zhang
Junyu Shi
Minghui Li
Xiaogeng Liu
Wei Wan
Hai Jin
AAML
482
36
0
15 Jul 2023
Going Further: Flatness at the Rescue of Early Stopping for Adversarial
  Example Transferability
Going Further: Flatness at the Rescue of Early Stopping for Adversarial Example Transferability
Martin Gubri
Maxime Cordy
Yves Le Traon
AAML
283
3
1
05 Apr 2023
Making Substitute Models More Bayesian Can Enhance Transferability of
  Adversarial Examples
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial ExamplesInternational Conference on Learning Representations (ICLR), 2023
Qizhang Li
Yiwen Guo
W. Zuo
Hao Chen
AAML
606
44
0
10 Feb 2023
LGV: Boosting Adversarial Example Transferability from Large Geometric
  Vicinity
LGV: Boosting Adversarial Example Transferability from Large Geometric VicinityEuropean Conference on Computer Vision (ECCV), 2022
Martin Gubri
Maxime Cordy
Mike Papadakis
Yves Le Traon
Koushik Sen
AAML
277
68
0
26 Jul 2022
1
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