Hybrid Zonotopes Exactly Represent ReLU Neural Networks
Author:
Affiliation:
1. The University of Texas at Dallas,Department of Mechanical Engineering
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10383192/10383193/10383944.pdf?arnumber=10383944
Reference21 articles.
1. Hybrid zonotopes: A new set representation for reachability analysis of mixed logical dynamical systems
2. Reachability Analysis and Safety Verification of Neural Feedback Systems via Hybrid Zonotopes
3. Towards fast computation of certified robustness for relu networks;Weng,2018
4. Efficiently computing local lipschitz constants of neural networks via bound propagation;Shi;arXiv preprint,2022
5. Efficient and accurate estimation of lipschitz constants for deep neural networks;Fazlyab,2019
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1. Hybrid Zonotope-Based Backward Reachability Analysis for Neural Feedback Systems With Nonlinear Plant Models;2024 American Control Conference (ACC);2024-07-10
2. zonoLAB: A MATLAB Toolbox for Set-Based Control Systems Analysis Using Hybrid Zonotopes;2024 American Control Conference (ACC);2024-07-10
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