Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher
Precision and Faster Verification

Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification

26 February 2019

Papers citing "Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification"

16 / 16 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 24 6 0 20 Jul 2023
A Neurosymbolic Approach to the Verification of Temporal Logic Properties of Learning enabled Control Systems Navid Hashemi Bardh Hoxha Tomoya Yamaguchi Danil Prokhorov Geogios Fainekos Jyotirmoy Deshmukh 25 7 0 07 Mar 2023
OccRob: Efficient SMT-Based Occlusion Robustness Verification of Deep Neural Networks Xingwu Guo Ziwei Zhou Yueling Zhang Guy Katz M. Zhang AAML 37 5 0 27 Jan 2023
QEBVerif: Quantization Error Bound Verification of Neural Networks Yedi Zhang Fu Song Jun Sun MQ 20 11 0 06 Dec 2022
Efficient Adversarial Input Generation via Neural Net Patching Tooba Khan Kumar Madhukar Subodh Vishnu Sharma AAML 18 0 0 30 Nov 2022
Verifying And Interpreting Neural Networks using Finite Automata Marco Salzer Eric Alsmann Florian Bruse M. Lange AAML 25 3 0 02 Nov 2022
PRoA: A Probabilistic Robustness Assessment against Functional Perturbations Tianle Zhang Wenjie Ruan J. Fieldsend AAML 13 21 0 05 Jul 2022
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 30 65 0 26 Jul 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 39 55 0 06 Apr 2021
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs Christopher Brix T. Noll AAML 25 10 0 16 Jun 2020
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
Algorithms for Verifying Deep Neural Networks Changliu Liu Tomer Arnon Christopher Lazarus Christopher A. Strong Clark W. Barrett Mykel J. Kochenderfer AAML 30 390 0 15 Mar 2019
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 88 292 0 09 Aug 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 231 1,837 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016