Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance

30 November 2021

Papers citing "Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance"

8 / 8 papers shown

Title
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems Saddek Bensalem Chih-Hong Cheng Wei Huang Xiaowei Huang Changshun Wu Xingyu Zhao AAML 27 6 0 20 Jul 2023
Hierarchical Distribution-Aware Testing of Deep Learning Wei Huang Xingyu Zhao Alec Banks V. Cox Xiaowei Huang OOD AAML 39 10 0 17 May 2022
Distribution-Aware Testing of Neural Networks Using Generative Models Swaroopa Dola Matthew B. Dwyer M. Soffa 32 52 0 26 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 86 475 0 02 Feb 2021
A Safety Framework for Critical Systems Utilising Deep Neural Networks Xingyu Zhao Alec Banks James Sharp Valentin Robu David Flynn Michael Fisher Xiaowei Huang AAML 50 48 0 07 Mar 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 249 1,838 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,842 0 08 Jul 2016