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Disentangling Adversarial Robustness and Generalization

3 December 2018

David Stutz

Matthias Hein

Bernt Schiele

AAML

OOD

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Papers citing "Disentangling Adversarial Robustness and Generalization"

30 / 180 papers shown

Title
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 84 92 0 05 May 2020
Robust Generative Adversarial Network Shufei Zhang Zhuang Qian Kaizhu Huang Jimin Xiao Yuan He 64 9 0 28 Apr 2020
Towards Feature Space Adversarial Attack Qiuling Xu Guanhong Tao Shuyang Cheng Xinming Zhang GAN AAML 66 25 0 26 Apr 2020
Adversarial Training for Large Neural Language Models Xiaodong Liu Hao Cheng Pengcheng He Weizhu Chen Yu Wang Hoifung Poon Jianfeng Gao AAML 83 186 0 20 Apr 2020
Learning to Learn Single Domain Generalization Fengchun Qiao Long Zhao Xi Peng OOD 132 444 0 30 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 191 102 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 151 75 0 15 Mar 2020
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks Siqi Liu A. Setio Florin-Cristian Ghesu Eli Gibson Sasa Grbic Bogdan Georgescu Dorin Comaniciu AAML OOD 117 40 0 08 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 126 67 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 103 69 0 25 Feb 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 56 0 0 25 Feb 2020
Adversarial Perturbations Prevail in the Y-Channel of the YCbCr Color Space Camilo Pestana Naveed Akhtar Wei Liu D. Glance Ajmal Mian AAML 57 10 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 84 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 92 52 0 20 Dec 2019
Explaining Classifiers using Adversarial Perturbations on the Perceptual Ball Andrew Elliott Stephen Law Chris Russell AAML 52 4 0 19 Dec 2019
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 125 30 0 16 Dec 2019
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples Nils Lukas Yuxuan Zhang Florian Kerschbaum MLAU FedML AAML 112 146 0 02 Dec 2019
Adversarial Examples Improve Image Recognition Cihang Xie Mingxing Tan Boqing Gong Jiang Wang Alan Yuille Quoc V. Le AAML 165 567 0 21 Nov 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 89 5 0 14 Oct 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 79 680 0 17 Sep 2019
Random Directional Attack for Fooling Deep Neural Networks Wenjian Luo Chenwang Wu Nan Zhou Li Ni AAML 19 4 0 06 Aug 2019
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness Walt Woods Jack H Chen C. Teuscher AAML 66 46 0 07 Jun 2019
Understanding Adversarial Behavior of DNNs by Disentangling Non-Robust and Robust Components in Performance Metric Yujun Shi B. Liao Guangyong Chen Yun-Hai Liu Ming-Ming Cheng Jiashi Feng AAML 20 2 0 06 Jun 2019
Meta Dropout: Learning to Perturb Features for Generalization Haebeom Lee Taewook Nam Eunho Yang Sung Ju Hwang OOD 68 3 0 30 May 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 104 1,846 0 06 May 2019
Bridging Adversarial Robustness and Gradient Interpretability Beomsu Kim Junghoon Seo Taegyun Jeon AAML 84 40 0 27 Mar 2019
Robustness of Generalized Learning Vector Quantization Models against Adversarial Attacks S. Saralajew Lars Holdijk Maike Rees T. Villmann OOD 49 19 0 01 Feb 2019
Face Hallucination Revisited: An Exploratory Study on Dataset Bias Klemen Grm Martin Pernuš Leo Cluzel Walter J. Scheirer Simon Dobrišek Vitomir Štruc CVBM 114 11 0 21 Dec 2018
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 187 559 0 13 Dec 2018
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 194 601 0 31 Oct 2017