D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, and T. A. Henzinger, “Compositional policy learning in stochastic control systems with formal guarantees,” in 37th Conference on Neural Information Processing Systems, New Orleans, LO, United States, 2023.

M. Chalupa and T. A. Henzinger, “Monitoring hyperproperties with prefix transducers,” in 23nd International Conference on Runtime Verification, Thessaloniki, Greek, 2023, vol. 14245, pp. 168–190.

M. Chalupa and T. A. Henzinger, “Monitoring hyperproperties with prefix transducers.” Zenodo, 2023.

T. A. Henzinger, M. Karimi, K. Kueffner, and K. Mallik, “Runtime monitoring of dynamic fairness properties,” in FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, Chicago, IL, United States, 2023, pp. 604–614.

E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Flavors of sequential information flow,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Philadelphia, PA, United States, 2022, vol. 13182, pp. 1–19.

A. Brunnbauer et al., “Latent imagination facilitates zero-shot transfer in autonomous racing,” in 2022 International Conference on Robotics and Automation, Philadelphia, PA, United States, 2022, pp. 7513–7520.

M. Garcia Soto, T. A. Henzinger, and C. Schilling, “Synthesis of parametric hybrid automata from time series,” in 20th International Symposium on Automated Technology for Verification and Analysis, Virtual, 2022, vol. 13505, pp. 337–353.

T. A. Henzinger, K. Lehtinen, and P. Totzke, “History-deterministic timed automata,” in 33rd International Conference on Concurrency Theory, Warsaw, Poland, 2022, vol. 243, p. 14:1-14:21.

G. Avni and T. A. Henzinger, “An updated survey of bidding games on graphs,” in 47th International Symposium on Mathematical Foundations of Computer Science, Vienna, Austria, 2022, vol. 241, p. 3:1-3:6.

M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” arXiv. .

T. A. Henzinger, “Quantitative monitoring of software,” in Software Verification, New Haven, CT, United States, 2022, vol. 13124, pp. 3–6.

E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Information-flow interfaces,” in Fundamental Approaches to Software Engineering, Munich, Germany, 2022, vol. 13241, pp. 3–22.

T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Abstract monitors for quantitative specifications,” in 22nd International Conference on Runtime Verification, Tbilisi, Georgia, 2022, vol. 13498, pp. 200–220.

R. Hasani et al., “Closed-form continuous-time neural networks,” Nature Machine Intelligence, vol. 4, no. 11. Springer Nature, pp. 992–1003, 2022.

M. Lechner, “Learning verifiable representations,” Institute of Science and Technology Austria, 2022.

K. Doveri, P. Ganty, and N. A. Mazzocchi, “FORQ-based language inclusion formal testing,” in Computer Aided Verification, Haifa, Israel, 2022, vol. 13372, pp. 109–129.

S. Bose, T. A. Henzinger, K. Lehtinen, S. Schewe, and P. Totzke, “History-deterministic timed automata are not determinizable,” in 16th International Conference on Reachability Problems, Kaiserslautern, Germany, 2022, vol. 13608, pp. 67–76.

S. A. Gruenbacher et al., “GoTube: Scalable statistical verification of continuous-depth models,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 6. Association for the Advancement of Artificial Intelligence, pp. 6755–6764, 2022.

M. Lechner, D. Zikelic, K. Chatterjee, and T. A. Henzinger, “Stability verification in stochastic control systems via neural network supermartingales,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 7. Association for the Advancement of Artificial Intelligence, pp. 7326–7336, 2022.

D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing policies in stochastic control systems,” arXiv. .