Specification-Guided Safety Verification for Feedforward Neural Networks

14 December 2018

Papers citing "Specification-Guided Safety Verification for Feedforward Neural Networks"

8 / 8 papers shown

Title
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Mohamed Bennai Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 81 100 0 04 Jan 2021
Abstraction based Output Range Analysis for Neural Networks P. Prabhakar Zahra Rahimi Afzal 38 62 0 18 Jul 2020
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems Hoang-Dung Tran Xiaodong Yang Diego Manzanas Lopez Patrick Musau L. V. Nguyen Weiming Xiang Stanley Bak Taylor T. Johnson 34 239 0 12 Apr 2020
Verification of Deep Convolutional Neural Networks Using ImageStars Hoang-Dung Tran Stanley Bak Weiming Xiang Taylor T. Johnson AAML 20 127 0 12 Apr 2020
Algorithms for Verifying Deep Neural Networks Changliu Liu Tomer Arnon Christopher Lazarus Christopher A. Strong Clark W. Barrett Mykel J. Kochenderfer AAML 41 394 0 15 Mar 2019
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 88 293 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 251 1,842 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 932 0 21 Oct 2016