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Motivating the Rules of the Game for Adversarial Example Research

18 July 2018

Justin Gilmer

Papers citing "Motivating the Rules of the Game for Adversarial Example Research"

50 / 86 papers shown

Title
Human Aligned Compression for Robust Models Samuel Räber Andreas Plesner Till Aczél Roger Wattenhofer AAML 99 0 0 16 Apr 2025
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 94 73 0 07 Aug 2020
Gradient Adversarial Training of Neural Networks Ayan Sinha Zhao Chen Vijay Badrinarayanan Andrew Rabinovich AAML 54 33 0 21 Jun 2018
Sufficient Conditions for Idealised Models to Have No Adversarial Examples: a Theoretical and Empirical Study with Bayesian Neural Networks Y. Gal Lewis Smith AAML BDL 83 35 0 02 Jun 2018
Detecting Adversarial Examples via Key-based Network Pinlong Zhao Zhouyu Fu Ou Wu Q. Hu Jun Wang AAML GAN 32 8 0 02 Jun 2018
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders Partha Ghosh Arpan Losalka Michael J. Black AAML 46 78 0 31 May 2018
Scaling provable adversarial defenses Eric Wong Frank R. Schmidt J. H. Metzen J. Zico Kolter AAML 78 449 0 31 May 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 104 1,783 0 30 May 2018
Defending Against Adversarial Attacks by Leveraging an Entire GAN G. Santhanam Paulina Grnarova AAML 43 40 0 27 May 2018
Adversarially Robust Training through Structured Gradient Regularization Kevin Roth Aurelien Lucchi Sebastian Nowozin Thomas Hofmann 65 23 0 22 May 2018
Bidirectional Learning for Robust Neural Networks S. Pontes-Filho Marcus Liwicki 61 9 0 21 May 2018
Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference Ruying Bao Sihang Liang Qingcan Wang GAN AAML 59 13 0 21 May 2018
Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks Jiefeng Chen Xi Wu Vaibhav Rastogi Yingyu Liang S. Jha AAML 49 22 0 20 May 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 84 1,178 0 17 May 2018
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations Alex Lamb Jonathan Binas Anirudh Goyal Dmitriy Serdyuk Sandeep Subramanian Ioannis Mitliagkas Yoshua Bengio OOD 81 43 0 07 Apr 2018
Defending against Adversarial Images using Basis Functions Transformations Uri Shaham J. Garritano Yutaro Yamada Ethan Weinberger A. Cloninger Xiuyuan Cheng Kelly P. Stanton Y. Kluger AAML 54 57 0 28 Mar 2018
Detecting Adversarial Perturbations with Saliency Chiliang Zhang Zhimou Yang Zuochang Ye AAML 31 32 0 23 Mar 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 98 628 0 16 Mar 2018
Combating Adversarial Attacks Using Sparse Representations S. Gopalakrishnan Zhinus Marzi Upamanyu Madhow Ramtin Pedarsani AAML 31 24 0 11 Mar 2018
Stochastic Activation Pruning for Robust Adversarial Defense Guneet Singh Dhillon Kamyar Azizzadenesheli Zachary Chase Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar AAML 81 547 0 05 Mar 2018
Robustness of Rotation-Equivariant Networks to Adversarial Perturbations Beranger Dumont Simona Maggio Pablo Montalvo AAML 49 24 0 19 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 105 308 0 12 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 234 3,194 0 01 Feb 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 113 969 0 29 Jan 2018
Sparsity-based Defense against Adversarial Attacks on Linear Classifiers Zhinus Marzi S. Gopalakrishnan Upamanyu Madhow Ramtin Pedarsani AAML 44 31 0 15 Jan 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Y. Zhang Phillip Isola Alexei A. Efros Eli Shechtman Oliver Wang EGVM 377 11,877 0 11 Jan 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Xingjun Ma Yue Liu Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck Basel Alomair Michael E. Houle James Bailey AAML 111 739 0 08 Jan 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text Nicholas Carlini D. Wagner AAML 97 1,083 0 05 Jan 2018
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 80 1,097 0 27 Dec 2017
When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time David J. Miller Yujia Wang G. Kesidis AAML 48 43 0 18 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 130 1,410 0 08 Dec 2017
Exploring the Landscape of Spatial Robustness Logan Engstrom Brandon Tran Dimitris Tsipras Ludwig Schmidt Aleksander Madry AAML 78 363 0 07 Dec 2017
Measuring the tendency of CNNs to Learn Surface Statistical Regularities Jason Jo Yoshua Bengio AAML 71 250 0 30 Nov 2017
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training Xi Wu Uyeong Jang Jiefeng Chen Lingjiao Chen S. Jha AAML 75 21 0 21 Nov 2017
Machine vs Machine: Minimax-Optimal Defense Against Adversarial Examples Jihun Hamm Akshay Mehra AAML 43 7 0 12 Nov 2017
LatentPoison - Adversarial Attacks On The Latent Space Antonia Creswell Anil A. Bharath B. Sengupta AAML OOD 52 20 0 08 Nov 2017
Intriguing Properties of Adversarial Examples E. D. Cubuk Barret Zoph S. Schoenholz Quoc V. Le AAML 64 85 0 08 Nov 2017
Mitigating Adversarial Effects Through Randomization Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille AAML 113 1,061 0 06 Nov 2017
HyperNetworks with statistical filtering for defending adversarial examples Zhun Sun Mete Ozay Takayuki Okatani AAML 44 16 0 06 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 120 1,406 0 31 Oct 2017
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples Yang Song Taesup Kim Sebastian Nowozin Stefano Ermon Nate Kushman AAML 110 791 0 30 Oct 2017
Attacking the Madry Defense Model with $L_1$ -based Adversarial Examples Yash Sharma Pin-Yu Chen 88 118 0 30 Oct 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 125 864 0 29 Oct 2017
Standard detectors aren't (currently) fooled by physical adversarial stop signs Jiajun Lu Hussein Sibai Evan Fabry David A. Forsyth AAML 57 59 0 09 Oct 2017
Security Evaluation of Pattern Classifiers under Attack Battista Biggio Giorgio Fumera Fabio Roli AAML 67 444 0 02 Sep 2017
Robust Physical-World Attacks on Deep Learning Models Kevin Eykholt Ivan Evtimov Earlence Fernandes Yue Liu Amir Rahmati Chaowei Xiao Atul Prakash Tadayoshi Kohno Basel Alomair AAML 57 595 0 27 Jul 2017
Adversarial Examples for Evaluating Reading Comprehension Systems Robin Jia Percy Liang AAML ELM 201 1,608 0 23 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 310 12,117 0 19 Jun 2017
MAT: A Multi-strength Adversarial Training Method to Mitigate Adversarial Attacks Chang Song Hsin-Pai Cheng Huanrui Yang Sicheng Li Chunpeng Wu Qing Wu H. Li Yiran Chen AAML 50 2 0 27 May 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 48 1,208 0 25 May 2017