Efficient and Transferable Adversarial Examples from Bayesian Neural Networks

10 November 2020

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

8 / 8 papers shown

Title
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 33 2 0 09 Oct 2024
PubDef: Defending Against Transfer Attacks From Public Models Chawin Sitawarin Jaewon Chang David Huang Wesson Altoyan David A. Wagner AAML 29 5 0 26 Oct 2023
Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training Yechao Zhang Shengshan Hu Leo Yu Zhang Junyu Shi Minghui Li Xiaogeng Liu Wei Wan Hai Jin AAML 22 21 0 15 Jul 2023
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples Qizhang Li Yiwen Guo W. Zuo Hao Chen AAML 27 35 0 10 Feb 2023
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity Martin Gubri Maxime Cordy Mike Papadakis Yves Le Traon Koushik Sen AAML 22 51 0 26 Jul 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 294 10,216 0 16 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 272 5,833 0 08 Jul 2016