Metrics and methods for robustness evaluation of neural networks with generative models

4 March 2020

Papers citing "Metrics and methods for robustness evaluation of neural networks with generative models"

7 / 7 papers shown

Title
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 43 8 0 03 Nov 2020
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 108 138 0 29 Nov 2018
Constructing Unrestricted Adversarial Examples with Generative Models Yang Song Rui Shu Nate Kushman Stefano Ermon GAN AAML 185 302 0 21 May 2018
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 42 87 0 02 Oct 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 228 1,835 0 03 Feb 2017
Conditional Image Synthesis With Auxiliary Classifier GANs Augustus Odena C. Olah Jonathon Shlens GAN 238 3,190 0 30 Oct 2016
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016