Henzinger TA, Karimi M, Kueffner K, Mallik K. Runtime monitoring of dynamic fairness properties. In: FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery; 2023:604-614. doi:10.1145/3593013.3594028

Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Flavors of sequential information flow. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 13182. Springer Nature; 2022:1-19. doi:10.1007/978-3-030-94583-1_1

Brunnbauer A, Berducci L, Brandstatter A, et al. Latent imagination facilitates zero-shot transfer in autonomous racing. In: 2022 International Conference on Robotics and Automation. IEEE; 2022:7513-7520. doi:10.1109/ICRA46639.2022.9811650

Garcia Soto M, Henzinger TA, Schilling C. Synthesis of parametric hybrid automata from time series. In: 20th International Symposium on Automated Technology for Verification and Analysis. Vol 13505. Springer Nature; 2022:337-353. doi:10.1007/978-3-031-19992-9_22

Henzinger TA, Lehtinen K, Totzke P. History-deterministic timed automata. In: 33rd International Conference on Concurrency Theory. Vol 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:14:1-14:21. doi:10.4230/LIPIcs.CONCUR.2022.14

Avni G, Henzinger TA. An updated survey of bidding games on graphs. In: 47th International Symposium on Mathematical Foundations of Computer Science. Vol 241. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:3:1-3:6. doi:10.4230/LIPIcs.MFCS.2022.3

Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv. doi:10.48550/arXiv.2204.07373

Henzinger TA. Quantitative monitoring of software. In: Software Verification. Vol 13124. LNCS. Springer Nature; 2022:3-6. doi:10.1007/978-3-030-95561-8_1

Henzinger TA, Mazzocchi NA, Sarac NE. Abstract monitors for quantitative specifications. In: 22nd International Conference on Runtime Verification. Vol 13498. Springer Nature; 2022:200-220. doi:10.1007/978-3-031-17196-3_11

Hasani R, Lechner M, Amini A, et al. Closed-form continuous-time neural networks. Nature Machine Intelligence. 2022;4(11):992-1003. doi:10.1038/s42256-022-00556-7

Lechner M. Learning verifiable representations. 2022. doi:10.15479/at:ista:11362

Doveri K, Ganty P, Mazzocchi NA. FORQ-based language inclusion formal testing. In: Computer Aided Verification. Vol 13372. Springer Nature; 2022:109-129. doi:10.1007/978-3-031-13188-2_6

Bose S, Henzinger TA, Lehtinen K, Schewe S, Totzke P. History-deterministic timed automata are not determinizable. In: 16th International Conference on Reachability Problems. Vol 13608. Springer Nature; 2022:67-76. doi:10.1007/978-3-031-19135-0_5

Gruenbacher SA, Lechner M, Hasani R, et al. GoTube: Scalable statistical verification of continuous-depth models. Proceedings of the AAAI Conference on Artificial Intelligence. 2022;36(6):6755-6764. doi:10.1609/aaai.v36i6.20631

Lechner M, Zikelic D, Chatterjee K, Henzinger TA. Stability verification in stochastic control systems via neural network supermartingales. Proceedings of the AAAI Conference on Artificial Intelligence. 2022;36(7):7326-7336. doi:10.1609/aaai.v36i7.20695

Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies in stochastic control systems. arXiv. doi:10.48550/arXiv.2205.11991

Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies for stochastic systems with reach-avoid guarantees. arXiv. doi:10.48550/ARXIV.2210.05308

Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Information-flow interfaces. In: Fundamental Approaches to Software Engineering. Vol 13241. Springer Nature; 2022:3-22. doi:10.1007/978-3-030-99429-7_1

Mühlböck F, Tate R. Transitioning from structural to nominal code with efficient gradual typing. Proceedings of the ACM on Programming Languages. 2021;5. doi:10.1145/3485504

Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. On the verification of neural ODEs with stochastic guarantees. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. AAAI Press; 2021:11525-11535.