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ARCH-COMP 2021 Category Report: Falsification with Validation of Results.

, , , , , , , , , , , , , , , , , и . ARCH@ADHS, том 80 из EPiC Series in Computing, стр. 133-152. EasyChair, (2021)

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Gray-box adversarial testing for control systems with machine learning components., и . HSCC, стр. 179-184. ACM, (2019)Worst-case Satisfaction of STL Specifications Using Feedforward Neural Network Controllers: A Lagrange Multipliers Approach., и . ACM Trans. Embed. Comput. Syst., 18 (5s): 107:1-107:20 (2019)Worst-case Satisfaction of STL Specifications Using Feedforward Neural Network Controllers: A Lagrange Multipliers Approach., и . ITA, стр. 1-20. IEEE, (2020)Falsification of Temporal Logic Requirements Using Gradient Based Local Search in Space and Time., и . ADHS, том 51 из IFAC-PapersOnLine, стр. 103-108. Elsevier, (2018)Hybrid approximate gradient and stochastic descent for falsification of nonlinear systems., и . ACC, стр. 529-534. IEEE, (2017)ARCH-COMP 2021 Category Report: Falsification with Validation of Results., , , , , , , , , и 8 other автор(ы). ARCH@ADHS, том 80 из EPiC Series in Computing, стр. 133-152. EasyChair, (2021)Encoding and monitoring responsibility sensitive safety rules for automated vehicles in signal temporal logic., , , , , , и . MEMOCODE, стр. 6:1-6:11. ACM, (2019)ARCH-COMP 2020 Category Report: Falsification., , , , , , , , , и 3 other автор(ы). ARCH, том 74 из EPiC Series in Computing, стр. 140-152. EasyChair, (2020)Functional gradient descent optimization for automatic test case generation for vehicle controllers., , , и . CASE, стр. 1059-1064. IEEE, (2017)Falsification of cyber-physical systems through multi-fidelity stochastic optimization., , , и . SNR, стр. 22-23. ACM, (2019)