PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples

30 October 2017

Papers citing "PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples"

23 / 123 papers shown

Title
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 15 15 0 05 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 28 3 0 01 Jun 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 11 97 0 25 May 2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks Yinpeng Dong Tianyu Pang Hang Su Jun Zhu SILM AAML 19 827 0 05 Apr 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 19 3 0 24 Mar 2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search Abhimanyu Dubey L. V. D. van der Maaten Zeki Yalniz Yixuan Li D. Mahajan AAML 22 62 0 05 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 31 40 0 03 Mar 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 27 175 0 13 Feb 2019
AutoGAN: Robust Classifier Against Adversarial Attacks Blerta Lindqvist Shridatt Sugrim R. Izmailov AAML 13 7 0 08 Dec 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou M. Guizani AAML 16 23 0 06 Nov 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 17 82 0 02 Oct 2018
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing Xiaofei Xie L. Ma Felix Juefei Xu Hongxu Chen Minhui Xue Bo-wen Li Yang Liu Jianjun Zhao Jianxiong Yin Simon See 32 40 0 04 Sep 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 41 226 0 18 Jul 2018
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders Partha Ghosh Arpan Losalka Michael J. Black AAML 9 77 0 31 May 2018
Defending Against Adversarial Attacks by Leveraging an Entire GAN G. Santhanam Paulina Grnarova AAML 11 40 0 27 May 2018
Towards the first adversarially robust neural network model on MNIST Lukas Schott Jonas Rauber Matthias Bethge Wieland Brendel AAML OOD 14 368 0 23 May 2018
Adversarial Defense based on Structure-to-Signal Autoencoders Joachim Folz Sebastián M. Palacio Jörn Hees Damian Borth Andreas Dengel AAML 23 31 0 21 Mar 2018
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training Derui Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 33 29 0 14 Mar 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 23 174 0 26 Dec 2017
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 22 350 0 06 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 35 418 0 02 Dec 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 233 2,547 0 25 Jan 2016