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Safety Verification of Deep Neural Networks

21 October 2016

Min Wu

Papers citing "Safety Verification of Deep Neural Networks"

48 / 448 papers shown

Title
Verifiable Reinforcement Learning via Policy Extraction Osbert Bastani Yewen Pu Armando Solar-Lezama OffRL 151 339 0 22 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 76 41 0 14 May 2018
Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems Chih-Hong Cheng Chung-Hao Huang Hirotoshi Yasuoka 49 41 0 11 May 2018
Reachability Analysis of Deep Neural Networks with Provable Guarantees Wenjie Ruan Xiaowei Huang Marta Kwiatkowska AAML 76 271 0 06 May 2018
Concolic Testing for Deep Neural Networks Youcheng Sun Min Wu Wenjie Ruan Xiaowei Huang Marta Kwiatkowska Daniel Kroening 99 335 0 30 Apr 2018
Formal Security Analysis of Neural Networks using Symbolic Intervals Shiqi Wang Kexin Pei Justin Whitehouse Junfeng Yang Suman Jana AAML 86 478 0 28 Apr 2018
Semantic Adversarial Deep Learning Sanjit A. Seshia S. Jha T. Dreossi AAML SILM 77 91 0 19 Apr 2018
Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components Cumhur Erkan Tuncali Georgios Fainekos Hisahiro Ito J. Kapinski 81 183 0 18 Apr 2018
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the $L_0$ Norm Wenjie Ruan Min Wu Youcheng Sun Xiaowei Huang Daniel Kroening Marta Kwiatkowska AAML 65 39 0 16 Apr 2018
Reasoning about Safety of Learning-Enabled Components in Autonomous Cyber-physical Systems Cumhur Erkan Tuncali J. Kapinski Hisahiro Ito Jyotirmoy V. Deshmukh 73 42 0 11 Apr 2018
A Dual Approach to Scalable Verification of Deep Networks Krishnamurthy Dvijotham Dvijotham Robert Stanforth Sven Gowal Timothy A. Mann Pushmeet Kohli 70 399 0 17 Mar 2018
Testing Deep Neural Networks Youcheng Sun Xiaowei Huang Daniel Kroening James Sharp Matthew Hill Rob Ashmore AAML 88 219 0 10 Mar 2018
Improved Explainability of Capsule Networks: Relevance Path by Agreement Atefeh Shahroudnejad Arash Mohammadi Konstantinos N. Plataniotis AAML MedIm 50 62 0 27 Feb 2018
Constrained Image Generation Using Binarized Neural Networks with Decision Procedures S. Korneev Nina Narodytska Luca Pulina A. Tacchella Nikolaj S. Bjørner Shmuel Sagiv MQ 48 13 0 24 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 131 940 0 09 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 85 469 0 31 Jan 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 130 969 0 29 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 146 1,873 0 02 Jan 2018
Reachable Set Computation and Safety Verification for Neural Networks with ReLU Activations Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 57 99 0 21 Dec 2017
Adversarial Examples: Attacks and Defenses for Deep Learning Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li SILM AAML 149 1,628 0 19 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 139 1,410 0 08 Dec 2017
How to Learn a Model Checker Dung Phan Radu Grosu Nicola Paoletti S. Smolka Scott D. Stoller 16 0 0 05 Dec 2017
Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems Kexin Pei Linjie Zhu Yinzhi Cao Junfeng Yang Carl Vondrick Suman Jana AAML 111 103 0 05 Dec 2017
AI Safety Gridworlds Jan Leike Miljan Martic Victoria Krakovna Pedro A. Ortega Tom Everitt Andrew Lefrancq Laurent Orseau Shane Legg 140 255 0 27 Nov 2017
How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models Kathrin Grosse David Pfaff M. Smith Michael Backes AAML 82 9 0 17 Nov 2017
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 190 1,506 0 02 Nov 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 143 866 0 29 Oct 2017
Feature-Guided Black-Box Safety Testing of Deep Neural Networks Matthew Wicker Xiaowei Huang Marta Kwiatkowska AAML 77 235 0 21 Oct 2017
Verification of Binarized Neural Networks via Inter-Neuron Factoring Chih-Hong Cheng Georg Nührenberg Chung-Hao Huang Harald Ruess AAML 85 21 0 09 Oct 2017
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 141 87 0 02 Oct 2017
Provably Minimally-Distorted Adversarial Examples Nicholas Carlini Guy Katz Clark W. Barrett D. Dill AAML 105 89 0 29 Sep 2017
Output Range Analysis for Deep Neural Networks Souradeep Dutta Susmit Jha S. Sankaranarayanan A. Tiwari AAML 67 120 0 26 Sep 2017
Verifying Properties of Binarized Deep Neural Networks Nina Narodytska S. Kasiviswanathan L. Ryzhyk Shmuel Sagiv T. Walsh AAML 101 217 0 19 Sep 2017
An Analysis of ISO 26262: Using Machine Learning Safely in Automotive Software Rick Salay Rodrigo Queiroz Krzysztof Czarnecki 55 133 0 07 Sep 2017
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars Yuchi Tian Kexin Pei Suman Jana Baishakhi Ray AAML 97 1,365 0 28 Aug 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models Pin-Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho-Jui Hsieh AAML 115 1,894 0 14 Aug 2017
Systematic Testing of Convolutional Neural Networks for Autonomous Driving T. Dreossi Shromona Ghosh Alberto L. Sangiovanni-Vincentelli Sanjit A. Seshia 92 61 0 10 Aug 2017
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 148 294 0 09 Aug 2017
Efficient Defenses Against Adversarial Attacks Valentina Zantedeschi Maria-Irina Nicolae Ambrish Rawat AAML 74 297 0 21 Jul 2017
An approach to reachability analysis for feed-forward ReLU neural networks A. Lomuscio Lalit Maganti 82 359 0 22 Jun 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 138 1,376 0 18 May 2017
Extending Defensive Distillation Nicolas Papernot Patrick McDaniel AAML 88 119 0 15 May 2017
Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks Rüdiger Ehlers 127 626 0 03 May 2017
Maximum Resilience of Artificial Neural Networks Chih-Hong Cheng Georg Nührenberg Harald Ruess AAML 145 284 0 28 Apr 2017
Compositional Falsification of Cyber-Physical Systems with Machine Learning Components T. Dreossi Alexandre Donzé Sanjit A. Seshia AAML 131 231 0 02 Mar 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 334 1,877 0 03 Feb 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 288 8,603 0 16 Aug 2016
Towards Verified Artificial Intelligence Sanjit A. Seshia Dorsa Sadigh S. Shankar Sastry 126 203 0 27 Jun 2016