Towards Understanding the Generative Capability of Adversarially Robust
Classifiers

Towards Understanding the Generative Capability of Adversarially Robust Classifiers

20 August 2021

Papers citing "Towards Understanding the Generative Capability of Adversarially Robust Classifiers"

11 / 11 papers shown

Title
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 265 689 0 19 Oct 2020
Smooth Adversarial Training Cihang Xie Mingxing Tan Boqing Gong Alan Yuille Quoc V. Le OOD 52 152 0 25 Jun 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 179 1,821 0 03 Mar 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 64 536 0 06 Dec 2019
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 54 977 0 29 Nov 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 146 3,803 0 12 Jul 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 90 752 0 31 May 2019
Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai Ziqiang Liu H. Dai Niao He Arthur Gretton Le Song Dale Schuurmans 47 53 0 27 Apr 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp Mitch Hill Song-Chun Zhu Ying Nian Wu 52 210 0 22 Apr 2019
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 199 3,110 0 09 Jul 2018
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 157 14,831 1 21 Dec 2013