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Taming Reachability Analysis of DNN-Controlled Systems via Abstraction-Based Training.

, , , , , and . VMCAI (2), volume 14500 of Lecture Notes in Computer Science, page 73-97. Springer, (2024)

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Wise Computing: Towards Endowing System Development with True Wisdom., , , and . CoRR, (2015)An SMT-Based Approach for Verifying Binarized Neural Networks., , , and . CoRR, (2020)Efficient Distributed Execution of Multi-component Scenario-Based Models., , , , , and . MODELSWARD (Revised Selected Papers), volume 880 of Communications in Computer and Information Science, page 449-483. Springer, (2017)Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks., , , , and . CAV (1), volume 10426 of Lecture Notes in Computer Science, page 97-117. Springer, (2017)Tighter Abstract Queries in Neural Network Verification., , , and . LPAR, volume 94 of EPiC Series in Computing, page 124-143. EasyChair, (2023)Guarded Deep Learning using Scenario-based Modeling.. MODELSWARD, page 126-136. SCITEPRESS, (2020)Towards Formal XAI: Formally Approximate Minimal Explanations of Neural Networks., and . TACAS (1), volume 13993 of Lecture Notes in Computer Science, page 187-207. Springer, (2023)Scenario-Based Modeling and Synthesis for Reactive Systems with Dynamic System Structure in ScenarioTools., , , and . D&P@MoDELS, volume 1725 of CEUR Workshop Proceedings, page 16-23. CEUR-WS.org, (2016)Invited Talk: Using SMT and Abstraction-Refinement for Neural Network Verification.. SMT, volume 2908 of CEUR Workshop Proceedings, page 1. CEUR-WS.org, (2021)Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates., , , , , , , , , and 2 other author(s). CoRR, (2024)