ReachNN: Reachability Analysis of Neural-Network Controlled Systems

ReachNN: Reachability Analysis of Neural-Network Controlled Systems

25 June 2019

Papers citing "ReachNN: Reachability Analysis of Neural-Network Controlled Systems"

19 / 19 papers shown

Title
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 35 8 0 07 Mar 2023
Automated Reachability Analysis of Neural Network-Controlled Systems via Adaptive Polytopes Taha Entesari Mahyar Fazlyab 40 5 0 14 Dec 2022
ReachLipBnB: A branch-and-bound method for reachability analysis of neural autonomous systems using Lipschitz bounds Taha Entesari Sina Sharifi Mahyar Fazlyab 52 6 0 01 Nov 2022
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction Edoardo Manino I. Bessa Lucas C. Cordeiro 23 1 0 21 Oct 2022
A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops Nicholas Rober Michael Everett Songan Zhang Jonathan P. How 37 9 0 14 Oct 2022
Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems Nicholas Rober Sydney M. Katz Chelsea Sidrane Esen Yel Michael Everett Mykel J. Kochenderfer Jonathan P. How 37 26 0 28 Sep 2022
Reachability Analysis of a General Class of Neural Ordinary Differential Equations Diego Manzanas Lopez Patrick Musau Nathaniel P. Hamilton Taylor T. Johnson 25 14 0 13 Jul 2022
Verification of Neural-Network Control Systems by Integrating Taylor Models and Zonotopes Christian Schilling M. Forets Sebastián Guadalupe 16 39 0 16 Dec 2021
Risk-averse autonomous systems: A brief history and recent developments from the perspective of optimal control Yuheng Wang Margaret P. Chapman 43 34 0 18 Sep 2021
Reachability Analysis of Neural Feedback Loops M. Everett Golnaz Habibi Chuangchuang Sun Jonathan P. How 21 53 0 09 Aug 2021
POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systems Chao Huang Jiameng Fan Zhilu Wang Yixuan Wang Weichao Zhou Jiajun Li Xin Chen Wenchao Li Qi Zhu 40 48 0 25 Jun 2021
Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe Panagiotis Vlantis Leila J. Bridgeman Michael M. Zavlanos 40 0 0 22 Jun 2021
Scalable Synthesis of Verified Controllers in Deep Reinforcement Learning Zikang Xiong Suresh Jagannathan 34 6 0 20 Apr 2021
Generating Probabilistic Safety Guarantees for Neural Network Controllers Sydney M. Katz Kyle D. Julian Christopher A. Strong Mykel J. Kochenderfer 42 6 0 01 Mar 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
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 183 933 0 21 Oct 2016