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385 Publications


2023 | Published | Conference Paper | IST-REx-ID: 13310 | OA
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.
[Published Version] View | Files available | DOI | arXiv
 

2023 | Published | Conference Paper | IST-REx-ID: 14076 | OA
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.
[Published Version] View | Files available | DOI
 

2023 | Published | Conference Paper | IST-REx-ID: 14242 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Published | Conference Paper | IST-REx-ID: 14243 | OA
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.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 

2023 | Published | Technical Report | IST-REx-ID: 12407 | OA
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.
[Published Version] View | Files available | DOI
 

2023 | Published | Conference Paper | IST-REx-ID: 12467 | OA
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.
[Published Version] View | Files available | DOI | arXiv
 

2023 | Published | Journal Article | IST-REx-ID: 12704 | OA
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.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2023 | Published | Conference Paper | IST-REx-ID: 12854 | OA
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.
[Published Version] View | Files available | DOI
 

2023 | Published | Conference Paper | IST-REx-ID: 12856 | OA
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.
[Published Version] View | Files available | DOI
 

2023 | Published | Journal Article | IST-REx-ID: 12876 | OA
N. Beneš, L. Brim, O. Huvar, S. Pastva, and D. Šafránek, “Boolean network sketches: A unifying framework for logical model inference,” Bioinformatics, vol. 39, no. 4. Oxford Academic, 2023.
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC
 

2022 | Published | Conference Paper | IST-REx-ID: 10774 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 | Published | Conference Paper | IST-REx-ID: 10891
T. A. Henzinger, “Quantitative monitoring of software,” in Software Verification, New Haven, CT, United States, 2022, vol. 13124, pp. 3–6.
View | DOI | WoS
 

2022 | Published | Conference Paper | IST-REx-ID: 11355 | OA
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.
[Published Version] View | Files available | DOI | WoS
 

2022 | Published | Thesis | PhD | IST-REx-ID: 11362 | OA
M. Lechner, “Learning verifiable representations,” Institute of Science and Technology Austria, 2022.
[Published Version] View | Files available | DOI
 

2022 | Submitted | Preprint | IST-REx-ID: 11366 | OA
M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2022 | Published | Conference Paper | IST-REx-ID: 11775 | OA
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.
[Published Version] View | Files available | DOI | WoS
 

2022 | Submitted | Preprint | IST-REx-ID: 14600 | OA
D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2022 | Submitted | Preprint | IST-REx-ID: 14601 | OA
D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing policies in stochastic control systems,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2022 | Published | Conference Paper | IST-REx-ID: 12010 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 | Published | Journal Article | IST-REx-ID: 12147 | OA
R. Hasani et al., “Closed-form continuous-time neural networks,” Nature Machine Intelligence, vol. 4, no. 11. Springer Nature, pp. 992–1003, 2022.
[Published Version] View | Files available | DOI | WoS | arXiv
 

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