G. Trinh, B. Benhamou, S. Pastva, and S. Soliman, “Scalable enumeration of trap spaces in boolean networks via answer set programming,” in Proceedings of the 38th AAAI Conference on Artificial Intelligence, 2024, vol. 38, no. 9, pp. 10714–10722.

M. Chalupa and T. A. Henzinger, “Bubaak: Runtime monitoring of program verifiers,” in Tools and Algorithms for the Construction and Analysis of Systems, Paris, France, 2023, vol. 13994, pp. 535–540.

M. Chalupa, F. Mühlböck, S. Muroya Lei, and T. A. Henzinger, “Vamos: Middleware for best-effort third-party monitoring,” in Fundamental Approaches to Software Engineering, Paris, France, 2023, vol. 13991, pp. 260–281.

M. Chalupa, F. Mühlböck, S. Muroya Lei, and T. A. Henzinger, VAMOS: Middleware for Best-Effort Third-Party Monitoring. Institute of Science and Technology Austria, 2023.

K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier framework for neural network controllers and certificates of stochastic systems,” in Tools and Algorithms for the Construction and Analysis of Systems , Paris, France, 2023, vol. 13993, pp. 3–25.

A. Anand, K. Mallik, S. P. Nayak, and A. K. Schmuck, “Computing adequately permissive assumptions for synthesis,” in TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, Paris, France, 2023, vol. 13994, pp. 211–228.

T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Quantitative safety and liveness,” in 26th International Conference Foundations of Software Science and Computation Structures, Paris, France, 2023, vol. 13992, pp. 349–370.

T. A. Henzinger, P. Kebis, N. A. Mazzocchi, and N. E. Sarac, “Regular methods for operator precedence languages,” in 50th International Colloquium on Automata, Languages, and Programming, Paderborn, Germany, 2023, vol. 261, p. 129:1--129:20.

M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” IEEE Robotics and Automation Letters, vol. 8, no. 3. Institute of Electrical and Electronics Engineers, pp. 1595–1602, 2023.

N. Benes, L. Brim, O. Huvar, S. Pastva, and D. Safránek, “Boolean network sketches: A unifying framework for logical model inference,” Bioinformatics, vol. 39, no. 4. Oxford Academic, 2023.

M. Lechner, D. Zikelic, K. Chatterjee, T. A. Henzinger, and D. Rus, “Quantization-aware interval bound propagation for training certifiably robust quantized neural networks,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United States, 2023, vol. 37, no. 12, pp. 14964–14973.

G. Avni, I. R. Jecker, and D. Zikelic, “Bidding graph games with partially-observable budgets,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United States, 2023, vol. 37, no. 5, pp. 5464–5471.

T. A. Henzinger, M. Karimi, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness,” in Computer Aided Verification, Paris, France, 2023, vol. 13965, pp. 358–382.

U. Boker, T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Safety and liveness of quantitative automata,” in 34th International Conference on Concurrency Theory, Antwerp, Belgium, 2023, vol. 279.

E. Bartocci, T. A. Henzinger, D. Nickovic, and A. Oliveira da Costa, “Hypernode automata,” in 34th International Conference on Concurrency Theory, Antwerp, Belgium, 2023, vol. 279.

T. A. Henzinger, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness under partial observations,” in 23rd International Conference on Runtime Verification, Thessaloniki, Greece, 2023, vol. 14245, pp. 291–311.

G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, and D. Zikelic, “Reachability poorman discrete-bidding games,” in Frontiers in Artificial Intelligence and Applications, Krakow, Poland, 2023, vol. 372, pp. 141–148.

M. Ansaripour, K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “Learning provably stabilizing neural controllers for discrete-time stochastic systems,” in 21st International Symposium on Automated Technology for Verification and Analysis, Singapore, Singapore, 2023, vol. 14215, pp. 357–379.

V. G. Trinh, B. Benhamou, T. A. Henzinger, and S. Pastva, “Trap spaces of multi-valued networks: Definition, computation, and applications,” Bioinformatics, vol. 39, no. Supplement_1. Oxford Academic, pp. i513–i522, 2023.

R. Majumdar, K. Mallik, A. K. Schmuck, and S. Soudjani, “Symbolic control for stochastic systems via finite parity games,” Nonlinear Analysis: Hybrid Systems, vol. 51. Elsevier, 2023.

S. Pastva and T. A. Henzinger, “Binary decision diagrams on modern hardware,” in Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design, Ames, IA, United States, 2023, pp. 122–131.

D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United States, 2023, vol. 37, no. 10, pp. 11926–11935.

K. Kueffner, A. Lukina, C. Schilling, and T. A. Henzinger, “Into the unknown: Active monitoring of neural networks (extended version),” International Journal on Software Tools for Technology Transfer, vol. 25. Springer Nature, pp. 575–592, 2023.

T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, and S. Soudjani, “Fast symbolic algorithms for mega-regular games under strong transition fairness,” TheoretiCS, vol. 2. EPI Sciences, 2023.

N. Benes, L. Brim, S. Pastva, D. Safránek, and E. Smijáková, “Phenotype control of partially specified boolean networks,” in 21st International Conference on Computational Methods in Systems Biology, Luxembourg City, Luxembourg, 2023, vol. 14137, pp. 18–35.

R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, and S. Soudjani, “A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties,” in 35th International Conference on Computer Aided Verification, Paris, France, 2023, vol. 13966, pp. 3–15.

R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, and S. Soudjani, “A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties.” Zenodo, 2023.

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. .

D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” arXiv. .

F. Mühlböck and R. Tate, “Transitioning from structural to nominal code with efficient gradual typing,” Proceedings of the ACM on Programming Languages, vol. 5. Association for Computing Machinery, 2021.

S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S. A. Smolka, and R. Grosu, “On the verification of neural ODEs with stochastic guarantees,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 13, pp. 11525–11535.