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Learning Lyapunov (Potential) Functions from Counterexamples and Demonstrations.

, and . Robotics: Science and Systems, (2017)

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Quantitative estimation of side-channel leaks with neural networks., , , and . Int. J. Softw. Tools Technol. Transf., 23 (4): 641-654 (2021)DC2: A framework for scalable, scope-bounded software verification., , , , , , , and . ASE, page 133-142. IEEE Computer Society, (2011)Multiple shooting, CEGAR-based falsification for hybrid systems., , , and . EMSOFT, page 5:1-5:10. ACM, (2014)Sherlock - A tool for verification of neural network feedback systems: demo abstract., , , , and . HSCC, page 262-263. ACM, (2019)Inputs of Coma: Static Detection of Denial-of-Service Vulnerabilities., , , , and . CSF, page 186-199. IEEE Computer Society, (2009)Integrating ICP and LRA solvers for deciding nonlinear real arithmetic problems., , , , , and . FMCAD, page 81-89. IEEE, (2010)Symbolic-Numeric Reachability Analysis of Hybrid Systems.. SNR@CAV, volume 37 of EPiC Series in Computing, page 1. EasyChair, (2015)Temporal Logic-Based Intent Monitoring for Mobile Robots., and . IROS, page 8643-8650. (2023)Program analysis via satisfiability modulo path programs., , , and . POPL, page 71-82. ACM, (2010)Verified Path Following Using Neural Control Lyapunov Functions., , , and . CoRL, volume 205 of Proceedings of Machine Learning Research, page 1949-1958. PMLR, (2022)