Disentangling Adversarial Robustness and Generalization

Disentangling Adversarial Robustness and Generalization

3 December 2018

Matthias Hein

Bernt Schiele

Papers citing "Disentangling Adversarial Robustness and Generalization"

17 / 67 papers shown

Title
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 19 91 0 05 May 2020
Towards Feature Space Adversarial Attack Qiuling Xu Guanhong Tao Shuyang Cheng Xinming Zhang GAN AAML 25 25 0 26 Apr 2020
Adversarial Training for Large Neural Language Models Xiaodong Liu Hao Cheng Pengcheng He Weizhu Chen Yu-Chiang Frank Wang Hoifung Poon Jianfeng Gao AAML 26 183 0 20 Apr 2020
Learning to Learn Single Domain Generalization Fengchun Qiao Long Zhao Xi Peng OOD 52 431 0 30 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 98 0 20 Mar 2020
Towards Face Encryption by Generating Adversarial Identity Masks Xiao Yang Yinpeng Dong Tianyu Pang Hang Su Jun Zhu YueFeng Chen H. Xue AAML PICV 29 72 0 15 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 58 63 0 02 Mar 2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min Lin Chen Amin Karbasi AAML 34 69 0 25 Feb 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 20 0 0 25 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 32 64 0 11 Feb 2020
Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation Yang He Shadi Rahimian Bernt Schiele Mario Fritz MIACV 13 49 0 20 Dec 2019
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 24 30 0 16 Dec 2019
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples Nils Lukas Yuxuan Zhang Florian Kerschbaum MLAU FedML AAML 31 144 0 02 Dec 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 40 552 0 13 Dec 2018
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 245 914 0 21 Apr 2018
RenderGAN: Generating Realistic Labeled Data Leon Sixt Benjamin Wild Tim Landgraf GAN 158 176 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016