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385 Publications
2023 |
Published |
Conference Paper |
IST-REx-ID: 13310 |
Henzinger, Thomas A, Mahyar Karimi, Konstantin Kueffner, and Kaushik Mallik. “Monitoring Algorithmic Fairness.” In Computer Aided Verification, 13965:358–382. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37703-7_17.
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| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14076 |
Chalupa, Marek, and Thomas A Henzinger. “Monitoring Hyperproperties with Prefix Transducers.” In 23nd International Conference on Runtime Verification, 14245:168–90. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44267-4_9.
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2023 |
Published |
Conference Paper |
IST-REx-ID: 14242 |
Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger, and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:14964–73. Association for the Advancement of Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i12.26747.
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| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14243 |
Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Bidding Graph Games with Partially-Observable Budgets.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:5464–71, 2023. https://doi.org/10.1609/aaai.v37i5.25679.
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| arXiv
2023 |
Published |
Technical Report |
IST-REx-ID: 12407 |
Chalupa, Marek, Fabian Mühlböck, Stefanie Muroya Lei, and Thomas A Henzinger. VAMOS: Middleware for Best-Effort Third-Party Monitoring. Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/AT:ISTA:12407.
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2023 |
Published |
Conference Paper |
IST-REx-ID: 12467 |
Henzinger, Thomas A, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Quantitative Safety and Liveness.” In 26th International Conference Foundations of Software Science and Computation Structures, 13992:349–70. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30829-1_17.
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| arXiv
2023 |
Published |
Journal Article |
IST-REx-ID: 12704 |
Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” IEEE Robotics and Automation Letters. Institute of Electrical and Electronics Engineers, 2023. https://doi.org/10.1109/LRA.2023.3240930.
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| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 12854 |
Chalupa, Marek, and Thomas A Henzinger. “Bubaak: Runtime Monitoring of Program Verifiers.” In Tools and Algorithms for the Construction and Analysis of Systems, 13994:535–40. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30820-8_32.
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2023 |
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Conference Paper |
IST-REx-ID: 12856 |
Chalupa, Marek, Fabian Mühlböck, Stefanie Muroya Lei, and Thomas A Henzinger. “Vamos: Middleware for Best-Effort Third-Party Monitoring.” In Fundamental Approaches to Software Engineering, 13991:260–81. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30826-0_15.
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2023 |
Published |
Journal Article |
IST-REx-ID: 12876 |
Beneš, Nikola, Luboš Brim, Ondřej Huvar, Samuel Pastva, and David Šafránek. “Boolean Network Sketches: A Unifying Framework for Logical Model Inference.” Bioinformatics. Oxford Academic, 2023. https://doi.org/10.1093/bioinformatics/btad158.
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| PubMed | Europe PMC
2022 |
Published |
Conference Paper |
IST-REx-ID: 10774 |
Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira 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), 13182:1–19. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-94583-1_1.
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| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 10891
Henzinger, Thomas A. “Quantitative Monitoring of Software.” In Software Verification, 13124:3–6. LNCS. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-95561-8_1.
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2022 |
Published |
Conference Paper |
IST-REx-ID: 11355 |
Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira Da Costa. “Information-Flow Interfaces.” In Fundamental Approaches to Software Engineering, 13241:3–22. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-99429-7_1.
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2022 |
Published |
Thesis | PhD |
IST-REx-ID: 11362 |
Lechner, Mathias. “Learning Verifiable Representations.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:11362.
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2022 |
Submitted |
Preprint |
IST-REx-ID: 11366 |
Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2204.07373.
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| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 11775 |
Henzinger, Thomas A, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Abstract Monitors for Quantitative Specifications.” In 22nd International Conference on Runtime Verification, 13498:200–220. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-17196-3_11.
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2022 |
Submitted |
Preprint |
IST-REx-ID: 14600 |
Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2210.05308.
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| arXiv
2022 |
Submitted |
Preprint |
IST-REx-ID: 14601 |
Zikelic, Dorde, Mathias Lechner, Krishnendu Chatterjee, and Thomas A Henzinger. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2205.11991.
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| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 12010 |
Brunnbauer, Axel, Luigi Berducci, Andreas Brandstatter, Mathias Lechner, Ramin Hasani, Daniela Rus, and Radu Grosu. “Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing.” In 2022 International Conference on Robotics and Automation, 7513–20. IEEE, 2022. https://doi.org/10.1109/ICRA46639.2022.9811650.
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| arXiv
2022 |
Published |
Journal Article |
IST-REx-ID: 12147 |
Hasani, Ramin, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, and Daniela Rus. “Closed-Form Continuous-Time Neural Networks.” Nature Machine Intelligence. Springer Nature, 2022. https://doi.org/10.1038/s42256-022-00556-7.
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