DeepSaucer: Unified Environment for Verifying Deep Neural Networks

9 November 2018

Papers citing "DeepSaucer: Unified Environment for Verifying Deep Neural Networks"

9 / 9 papers shown

Title
Identifying Implementation Bugs in Machine Learning based Image Classifiers using Metamorphic Testing Anurag Dwarakanath Manish Ahuja Samarth Sikand Raghotham M. Rao Jagadeesh Chandra J. C. Bose Neville Dubash Sanjay Podder VLM 33 176 0 16 Aug 2018
Testing Deep Neural Networks Youcheng Sun Xiaowei Huang Daniel Kroening James Sharp Matthew Hill Rob Ashmore AAML 59 219 0 10 Mar 2018
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 111 87 0 02 Oct 2017
Towards Proving the Adversarial Robustness of Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel J. Kochenderfer AAML OOD 80 118 0 08 Sep 2017
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars Yuchi Tian Kexin Pei Suman Jana Baishakhi Ray AAML 75 1,361 0 28 Aug 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 109 1,371 0 18 May 2017
Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks Rüdiger Ehlers 113 626 0 03 May 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 321 1,875 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 245 944 0 21 Oct 2016