Neural Network Compression of ACAS Xu Early Prototype is Unsafe: Closed-Loop Verification through Quantized State Backreachability

17 January 2022

Papers citing "Neural Network Compression of ACAS Xu Early Prototype is Unsafe: Closed-Loop Verification through Quantized State Backreachability"

10 / 10 papers shown

Title
Learning Verifiable Control Policies Using Relaxed Verification Puja Chaudhury Alexander Estornell Michael Everett 27 0 0 23 Apr 2025
AutoSpec: Automated Generation of Neural Network Specifications Shuowei Jin Francis Y. Yan Cheng Tan Anuj Kalia Xenofon Foukas Z. Morley Mao 35 0 0 17 Sep 2024
Formal Verification and Control with Conformal Prediction Lars Lindemann Yiqi Zhao Xinyi Yu George J. Pappas Jyotirmoy V. Deshmukh 57 13 0 31 Aug 2024
Provably Safe Neural Network Controllers via Differential Dynamic Logic Samuel Teuber Stefan Mitsch André Platzer AAML 22 8 0 16 Feb 2024
The inverse problem for neural networks M. Forets Christian Schilling 22 0 0 27 Aug 2023
DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops Michael Everett Rudy Bunel Shayegan Omidshafiei 8 9 0 09 Dec 2022
Conformal Prediction for STL Runtime Verification Lars Lindemann Xin Qin Jyotirmoy V. Deshmukh George J. Pappas 13 43 0 03 Nov 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 19 26 0 28 Sep 2022
GAS: Generating Fast and Accurate Surrogate Models for Autonomous Vehicle Systems Keyur Joshi Chiao Hsieh Sayan Mitra Sasa Misailovic 9 3 0 03 Aug 2022
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 222 1,818 0 03 Feb 2017