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Chalupa, M., &; Richter, C. (2024). Bubaak-SpLit: Split what you cannot verify (Competition contribution). In 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (Vol. 14572, pp. 353–358). Luxembourg City, Luxembourg: Springer Nature.https://doi.org/10.1007/978-3-031-57256-2_20 
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Avni, G., Mallik, K., &; Sadhukhan, S. (2024). Auction-based scheduling. In 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (Vol. 14572, pp. 153–172). Luxembourg City, Luxembourg: Springer Nature.https://doi.org/10.1007/978-3-031-57256-2_8 
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arXiv: 2310.11798

Majumdar, R., Saflam, I., &; Thejaswini, K. S. (2024). Rabin games and colourful universal trees. In 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (Vol. 14572, pp. 213–231). Springer Nature.https://doi.org/10.1007/978-3-031-57256-2_11 
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arXiv: 2401.07548

Chalupa, M., &; Henzinger, T. A. (2023). Bubaak: Runtime monitoring of program verifiers. In Tools and Algorithms for the Construction and Analysis of Systems (Vol. 13994, pp. 535–540). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-30820-8_32 
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Chalupa, M., Mühlböck, F., Muroya Lei, S., &; Henzinger, T. A. (2023). Vamos: Middleware for best-effort third-party monitoring. In Fundamental Approaches to Software Engineering (Vol. 13991, pp. 260–281). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-30826-0_15 
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Chalupa, M., Mühlböck, F., Muroya Lei, S., &; Henzinger, T. A. (2023). VAMOS: Middleware for Best-Effort Third-Party Monitoring. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:12407 
LibreCat: https://research-explorer.ista.ac.at/record/12407
DOI: 10.15479/AT:ISTA:12407

Chatterjee, K., Henzinger, T. A., Lechner, M., &; Zikelic, D. (2023). A learner-verifier framework for neural network controllers and certificates of stochastic systems. In Tools and Algorithms for the Construction and Analysis of Systems  (Vol. 13993, pp. 3–25). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-30823-9_1 
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Anand, A., Mallik, K., Nayak, S. P., &; Schmuck, A. K. (2023). Computing adequately permissive assumptions for synthesis. In TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems (Vol. 13994, pp. 211–228). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-30820-8_15 
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Henzinger, T. A., Mazzocchi, N. A., &; Sarac, N. E. (2023). Quantitative safety and liveness. In 26th International Conference Foundations of Software Science and Computation Structures (Vol. 13992, pp. 349–370). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-30829-1_17 
LibreCat: https://research-explorer.ista.ac.at/record/12467
DOI: 10.1007/978-3-031-30829-1_17
arXiv: 2301.11175

Henzinger, T. A., Kebis, P., Mazzocchi, N. A., &; Sarac, N. E. (2023). Regular methods for operator precedence languages. In 50th International Colloquium on Automata, Languages, and Programming (Vol. 261, p. 129:1--129:20). Paderborn, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.ICALP.2023.129 
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DOI: 10.4230/LIPIcs.ICALP.2023.129
arXiv: 2305.03447

Lechner, M., Amini, A., Rus, D., &; Henzinger, T. A. (2023). Revisiting the adversarial robustness-accuracy tradeoff in robot learning. IEEE Robotics and Automation Letters. Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/LRA.2023.3240930 
LibreCat: https://research-explorer.ista.ac.at/record/12704
DOI: 10.1109/LRA.2023.3240930
WoS: 000936534100012
arXiv: 2204.07373

Benes, N., Brim, L., Huvar, O., Pastva, S., &; Safránek, D. (2023). Boolean network sketches: A unifying framework for logical model inference. Bioinformatics. Oxford Academic.https://doi.org/10.1093/bioinformatics/btad158 
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DOI: 10.1093/bioinformatics/btad158
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PMID: 37004199

Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., &; Rus, D. (2023). Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 14964–14973). Washington, DC, United States: Association for the Advancement of Artificial Intelligence.https://doi.org/10.1609/aaai.v37i12.26747 
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arXiv: 2211.16187

Avni, G., Jecker, I. R., &; Zikelic, D. (2023). Bidding graph games with partially-observable budgets. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 5464–5471). Washington, DC, United States.https://doi.org/10.1609/aaai.v37i5.25679 
LibreCat: https://research-explorer.ista.ac.at/record/14243
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arXiv: 2211.13626

Henzinger, T. A., Karimi, M., Kueffner, K., &; Mallik, K. (2023). Monitoring algorithmic fairness. In Computer Aided Verification (Vol. 13965, pp. 358–382). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-37703-7_17 
LibreCat: https://research-explorer.ista.ac.at/record/13310
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arXiv: 2305.15979

Boker, U., Henzinger, T. A., Mazzocchi, N. A., &; Sarac, N. E. (2023). Safety and liveness of quantitative automata. In 34th International Conference on Concurrency Theory (Vol. 279). Antwerp, Belgium: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.CONCUR.2023.17 
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arXiv: 2307.06016

Bartocci, E., Henzinger, T. A., Nickovic, D., &; Oliveira da Costa, A. (2023). Hypernode automata. In 34th International Conference on Concurrency Theory (Vol. 279). Antwerp, Belgium: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.CONCUR.2023.21 
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arXiv: 2305.02836

Henzinger, T. A., Kueffner, K., &; Mallik, K. (2023). Monitoring algorithmic fairness under partial observations. In 23rd International Conference on Runtime Verification (Vol. 14245, pp. 291–311). Thessaloniki, Greece: Springer Nature.https://doi.org/10.1007/978-3-031-44267-4_15 
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arXiv: 2308.00341

Avni, G., Meggendorfer, T., Sadhukhan, S., Tkadlec, J., &; Zikelic, D. (2023). Reachability poorman discrete-bidding games. In Frontiers in Artificial Intelligence and Applications (Vol. 372, pp. 141–148). Krakow, Poland: IOS Press.https://doi.org/10.3233/FAIA230264 
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DOI: 10.3233/FAIA230264
arXiv: 2307.15218

Ansaripour, M., Chatterjee, K., Henzinger, T. A., Lechner, M., &; Zikelic, D. (2023). Learning provably stabilizing neural controllers for discrete-time stochastic systems. In 21st International Symposium on Automated Technology for Verification and Analysis (Vol. 14215, pp. 357–379). Singapore, Singapore: Springer Nature.https://doi.org/10.1007/978-3-031-45329-8_17 
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Trinh, V. G., Benhamou, B., Henzinger, T. A., &; Pastva, S. (2023). Trap spaces of multi-valued networks: Definition, computation, and applications. Bioinformatics. Oxford Academic.https://doi.org/10.1093/bioinformatics/btad262 
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PMID: 37387165

Majumdar, R., Mallik, K., Schmuck, A. K., &; Soudjani, S. (2023). Symbolic control for stochastic systems via finite parity games. Nonlinear Analysis: Hybrid Systems. Elsevier.https://doi.org/10.1016/j.nahs.2023.101430 
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DOI: 10.1016/j.nahs.2023.101430
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arXiv: 2101.00834

Pastva, S., &; Henzinger, T. A. (2023). Binary decision diagrams on modern hardware. In Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design (pp. 122–131). Ames, IA, United States: TU Vienna Academic Press.https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20 
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Zikelic, D., Lechner, M., Henzinger, T. A., &; Chatterjee, K. (2023). Learning control policies for stochastic systems with reach-avoid guarantees. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 11926–11935). Washington, DC, United States: Association for the Advancement of Artificial Intelligence.https://doi.org/10.1609/aaai.v37i10.26407 
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arXiv: 2210.05308

Kueffner, K., Lukina, A., Schilling, C., &; Henzinger, T. A. (2023). Into the unknown: Active monitoring of neural networks (extended version). International Journal on Software Tools for Technology Transfer. Springer Nature.https://doi.org/10.1007/s10009-023-00711-4 
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arXiv: 2009.06429

Banerjee, T., Majumdar, R., Mallik, K., Schmuck, A.-K., &; Soudjani, S. (2023). Fast symbolic algorithms for mega-regular games under strong transition fairness. TheoretiCS. EPI Sciences.https://doi.org/10.46298/theoretics.23.4 
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arXiv: 2202.07480

Benes, N., Brim, L., Pastva, S., Safránek, D., &; Smijáková, E. (2023). Phenotype control of partially specified boolean networks. In 21st International Conference on Computational Methods in Systems Biology (Vol. 14137, pp. 18–35). Luxembourg City, Luxembourg: Springer Nature.https://doi.org/10.1007/978-3-031-42697-1_2 
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Majumdar, R., Mallik, K., Rychlicki, M., Schmuck, A.-K., &; Soudjani, S. (2023). A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. In 35th International Conference on Computer Aided Verification (Vol. 13966, pp. 3–15). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-37709-9_1 
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Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., &; Henzinger, T. A. (2023). Compositional policy learning in stochastic control systems with formal guarantees. In 37th Conference on Neural Information Processing Systems. New Orleans, LO, United States.
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arXiv: 2312.01456

Chalupa, M., &; Henzinger, T. A. (2023). Monitoring hyperproperties with prefix transducers. In 23nd International Conference on Runtime Verification (Vol. 14245, pp. 168–190). Thessaloniki, Greek: Springer Nature.https://doi.org/10.1007/978-3-031-44267-4_9 
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Henzinger, T. A., Karimi, M., Kueffner, K., &; Mallik, K. (2023). Runtime monitoring of dynamic fairness properties. In FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 604–614). Chicago, IL, United States: Association for Computing Machinery.https://doi.org/10.1145/3593013.3594028 
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Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., &; Da Costa, A. O. (2022). 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, pp. 1–19). Philadelphia, PA, United States: Springer Nature.https://doi.org/10.1007/978-3-030-94583-1_1 
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arXiv: 2105.02013

Brunnbauer, A., Berducci, L., Brandstatter, A., Lechner, M., Hasani, R., Rus, D., &; Grosu, R. (2022). Latent imagination facilitates zero-shot transfer in autonomous racing. In 2022 International Conference on Robotics and Automation (pp. 7513–7520). Philadelphia, PA, United States: IEEE.https://doi.org/10.1109/ICRA46639.2022.9811650 
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arXiv: 2103.04909

Garcia Soto, M., Henzinger, T. A., &; Schilling, C. (2022). Synthesis of parametric hybrid automata from time series. In 20th International Symposium on Automated Technology for Verification and Analysis (Vol. 13505, pp. 337–353). Virtual: Springer Nature.https://doi.org/10.1007/978-3-031-19992-9_22 
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arXiv: 2208.06383

Henzinger, T. A., Lehtinen, K., &; Totzke, P. (2022). History-deterministic timed automata. In 33rd International Conference on Concurrency Theory (Vol. 243, p. 14:1-14:21). Warsaw, Poland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.CONCUR.2022.14 
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Avni, G., &; Henzinger, T. A. (2022). An updated survey of bidding games on graphs. In 47th International Symposium on Mathematical Foundations of Computer Science (Vol. 241, p. 3:1-3:6). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.MFCS.2022.3 
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Lechner, M., Amini, A., Rus, D., &; Henzinger, T. A. (n.d.). Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv.https://doi.org/10.48550/arXiv.2204.07373 
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Henzinger, T. A. (2022). Quantitative monitoring of software. In Software Verification (Vol. 13124, pp. 3–6). New Haven, CT, United States: Springer Nature.https://doi.org/10.1007/978-3-030-95561-8_1 
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Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., &; Da Costa, A. O. (2022). Information-flow interfaces. In Fundamental Approaches to Software Engineering (Vol. 13241, pp. 3–22). Munich, Germany: Springer Nature.https://doi.org/10.1007/978-3-030-99429-7_1 
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Henzinger, T. A., Mazzocchi, N. A., &; Sarac, N. E. (2022). Abstract monitors for quantitative specifications. In 22nd International Conference on Runtime Verification (Vol. 13498, pp. 200–220). Tbilisi, Georgia: Springer Nature.https://doi.org/10.1007/978-3-031-17196-3_11 
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Hasani, R., Lechner, M., Amini, A., Liebenwein, L., Ray, A., Tschaikowski, M.,https://doi.org/10.1038/s42256-022-00556-7__Rus, D. (2022). Closed-form continuous-time neural networks. Nature Machine Intelligence. Springer Nature.https://doi.org/10.1038/s42256-022-00556-7 
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Lechner, M. (2022). Learning verifiable representations. Institute of Science and Technology Austria.https://doi.org/10.15479/at:ista:11362 
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Doveri, K., Ganty, P., &; Mazzocchi, N. A. (2022). FORQ-based language inclusion formal testing. In Computer Aided Verification (Vol. 13372, pp. 109–129). Haifa, Israel: Springer Nature.https://doi.org/10.1007/978-3-031-13188-2_6 
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arXiv: 2207.13549

Bose, S., Henzinger, T. A., Lehtinen, K., Schewe, S., &; Totzke, P. (2022). History-deterministic timed automata are not determinizable. In 16th International Conference on Reachability Problems (Vol. 13608, pp. 67–76). Kaiserslautern, Germany: Springer Nature.https://doi.org/10.1007/978-3-031-19135-0_5 
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Gruenbacher, S. A., Lechner, M., Hasani, R., Rus, D., Henzinger, T. A., Smolka, S. A., &; Grosu, R. (2022). GoTube: Scalable statistical verification of continuous-depth models. Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence.https://doi.org/10.1609/aaai.v36i6.20631 
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DOI: 10.1609/aaai.v36i6.20631
arXiv: 2107.08467

Lechner, M., Zikelic, D., Chatterjee, K., &; Henzinger, T. A. (2022). Stability verification in stochastic control systems via neural network supermartingales. Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence.https://doi.org/10.1609/aaai.v36i7.20695 
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arXiv: 2112.09495

Zikelic, D., Lechner, M., Chatterjee, K., &; Henzinger, T. A. (n.d.). Learning stabilizing policies in stochastic control systems. arXiv.https://doi.org/10.48550/arXiv.2205.11991 
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arXiv: 2205.11991

Zikelic, D., Lechner, M., Henzinger, T. A., &; Chatterjee, K. (n.d.). Learning control policies for stochastic systems with reach-avoid guarantees. arXiv.https://doi.org/10.48550/ARXIV.2210.05308 
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Mühlböck, F., &; Tate, R. (2021). Transitioning from structural to nominal code with efficient gradual typing. Proceedings of the ACM on Programming Languages. Chicago, IL, United States: Association for Computing Machinery.https://doi.org/10.1145/3485504 
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Grunbacher, S., Hasani, R., Lechner, M., Cyranka, J., Smolka, S. A., &; Grosu, R. (2021). On the verification of neural ODEs with stochastic guarantees. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 11525–11535). Virtual: AAAI Press.
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arXiv: 2012.08863

Hasani, R., Lechner, M., Amini, A., Rus, D., &; Grosu, R. (2021). Liquid time-constant networks. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 7657–7666). Virtual: AAAI Press.
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Babaiee, Z., Hasani, R., Lechner, M., Rus, D., &; Grosu, R. (2021). On-off center-surround receptive fields for accurate and robust image classification. In Proceedings of the 38th International Conference on Machine Learning (Vol. 139, pp. 478–489). Virtual: ML Research Press.
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Vorbach, C. J., Hasani, R., Amini, A., Lechner, M., &; Rus, D. (2021). Causal navigation by continuous-time neural networks. In 35th Conference on Neural Information Processing Systems. Virtual.
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arXiv: 2106.08314

Kragl, B., &; Qadeer, S. (2021). The Civl verifier. In P. Ruzica &; M. W. Whalen (Eds.), Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design (Vol. 2, pp. 143–152). Virtual: TU Wien Academic Press.https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23 
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Dubach, G., &; Mühlböck, F. (n.d.). Formal verification of Zagier’s one-sentence proof. arXiv.https://doi.org/10.48550/arXiv.2103.11389 
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Henzinger, T. A., Lechner, M., &; Zikelic, D. (2021). Scalable verification of quantized neural networks. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 3787–3795). Virtual: AAAI Press.
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Lechner, M., dikeli, Ð., Chatterjee, K., &; Henzinger, T. A. (2021). Infinite time horizon safety of Bayesian neural networks. In 35th Conference on Neural Information Processing Systems. Virtual.https://doi.org/10.48550/arXiv.2111.03165 
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Sarac, N. E., Altun, Ö. F., Atam, K. T., Karahoda, S., Kaya, K., &; Yenigün, H. (2021). Boosting expensive synchronizing heuristics. Expert Systems with Applications. Elsevier.https://doi.org/10.1016/j.eswa.2020.114203 
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Garcia Soto, M., Henzinger, T. A., &; Schilling, C. (2021). Synthesis of hybrid automata with affine dynamics from time-series data. In HSCC ’21: Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control (p. 2102.12734). Nashville, TN, United States: Association for Computing Machinery.https://doi.org/10.1145/3447928.3456704 
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Avni, G., Henzinger, T. A., &; dikeli, . (2021). Bidding mechanisms in graph games. Journal of Computer and System Sciences. Elsevier.https://doi.org/10.1016/j.jcss.2021.02.008 
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Henzinger, T. A., &; Sarac, N. E. (2021). Quantitative and approximate monitoring. In Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. Online: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/LICS52264.2021.9470547 
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Petrov, T., Igler, C., Sezgin, A., Henzinger, T. A., &; Guet, C. C. (2021). Long lived transients in gene regulation. Theoretical Computer Science. Elsevier.https://doi.org/10.1016/j.tcs.2021.05.023 
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Mühlböck, F., &; Henzinger, T. A. (2021). Differential monitoring. In International Conference on Runtime Verification (Vol. 12974, pp. 231–243). Cham: Springer Nature.https://doi.org/10.1007/978-3-030-88494-9_12 
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Mühlböck, F., &; Henzinger, T. A. (2021). Differential monitoring. IST Austria.https://doi.org/10.15479/AT:ISTA:9946 
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Sietzen, S., Lechner, M., Borowski, J., Hasani, R., &; Waldner, M. (2021). Interactive analysis of CNN robustness. Computer Graphics Forum. Wiley.https://doi.org/10.1111/cgf.14418 
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Aghajohari, M., Avni, G., &; Henzinger, T. A. (2021). Determinacy in discrete-bidding infinite-duration games. Logical Methods in Computer Science. International Federation for Computational Logic.https://doi.org/10.23638/LMCS-17(1:10)2021 
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Lechner, M., Hasani, R., Grosu, R., Rus, D., &; Henzinger, T. A. (2021). Adversarial training is not ready for robot learning. In 2021 IEEE International Conference on Robotics and Automation (pp. 4140–4147). Xi’an, China.https://doi.org/10.1109/ICRA48506.2021.9561036 
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Lukina, A., Schilling, C., &; Henzinger, T. A. (2021). Into the unknown: active monitoring of neural networks. In 21st International Conference on Runtime Verification (Vol. 12974, pp. 42–61). Cham: Springer Nature.https://doi.org/10.1007/978-3-030-88494-9_3 
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Hasani, R., Lechner, M., Amini, A., Rus, D., &; Grosu, R. (2020). A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits. In Proceedings of the 37th International Conference on Machine Learning (pp. 4082–4093). Virtual.
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Ferrere, T., Henzinger, T. A., &; Kragl, B. (2020). Monitoring event frequencies. In 28th EACSL Annual Conference on Computer Science Logic (Vol. 152). Barcelona, Spain: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.CSL.2020.20 
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Althoff, M., Bak, S., Bao, Z., Forets, M., Frehse, G., Freire, D.,https://doi.org/10.29007/7dt2__Wetzlinger, M. (2020). ARCH-COM Category Report: Continuous and hybrid systems with linear dynamics. In EPiC Series in Computing (Vol. 74, pp. 16–48). EasyChair.https://doi.org/10.29007/7dt2 
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Geretti, L., Alexandre Dit Sandretto, J., Althoff, M., Benet, L., Chapoutot, A., Chen, X.,https://doi.org/10.29007/zkf6__Schilling, C. (2020). ARCH-COM Category Report: Continuous and hybrid systems with nonlinear dynamics. In EPiC Series in Computing (Vol. 74, pp. 49–75). EasyChair.https://doi.org/10.29007/zkf6 
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Chatterjee, K., Henzinger, T. A., &; Otop, J. (2020). Multi-dimensional long-run average problems for vector addition systems with states. In 31st International Conference on Concurrency Theory (Vol. 171). Virtual: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.CONCUR.2020.23 
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Avni, G., &; Henzinger, T. A. (2020). A survey of bidding games on graphs. In 31st International Conference on Concurrency Theory (Vol. 171). Virtual: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.CONCUR.2020.2 
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Alamdari, P. A., Avni, G., Henzinger, T. A., &; Lukina, A. (2020). Formal methods with a touch of magic. In Proceedings of the 20th Conference on Formal Methods in Computer-Aided Design (pp. 138–147). Online Conference: TU Wien Academic Press.https://doi.org/10.34727/2020/isbn.978-3-85448-042-6_21 
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Singh, S. P., &; Alistarh, D.-A. (2020). WoodFisher: Efficient second-order approximation for neural network compression. In Advances in Neural Information Processing Systems (Vol. 33, pp. 18098–18109). Vancouver, Canada: Curran Associates.
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Gruenbacher, S., Cyranka, J., Lechner, M., Islam, M. A., Smolka, S. A., &; Grosu, R. (2020). Lagrangian reachtubes: The next generation. In Proceedings of the 59th IEEE Conference on Decision and Control (Vol. 2020, pp. 1556–1563). Jeju Islang, Korea (South): IEEE.https://doi.org/10.1109/CDC42340.2020.9304042 
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Lechner, M. (2020). Learning representations for binary-classification without backpropagation. In 8th International Conference on Learning Representations. Virtualf; Addis Ababa, Ethiopia: ICLR.
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Giacobbe, M., Henzinger, T. A., &; Lechner, M. (2020). How many bits does it take to quantize your neural network? In International Conference on Tools and Algorithms for the Construction and Analysis of Systems (Vol. 12079, pp. 79–97). Dublin, Ireland: Springer Nature.https://doi.org/10.1007/978-3-030-45237-7_5 
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Avni, G., Henzinger, T. A., &; Kupferman, O. (2020). Dynamic resource allocation games. Theoretical Computer Science. Elsevier.https://doi.org/10.1016/j.tcs.2019.06.031 
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Henzinger, T. A., Lukina, A., &; Schilling, C. (2020). Outside the box: Abstraction-based monitoring of neural networks. In 24th European Conference on Artificial Intelligence (Vol. 325, pp. 2433–2440). Santiago de Compostela, Spain: IOS Press.https://doi.org/10.3233/FAIA200375 
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Baranowski, M., He, S., Lechner, M., Nguyen, T. S., &; Rakamari, Z. (2020). An SMT theory of fixed-point arithmetic. In Automated Reasoning (Vol. 12166, pp. 13–31). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-030-51074-9_2 
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Lechner, M., Hasani, R., Amini, A., Henzinger, T. A., Rus, D., &; Grosu, R. (2020). Neural circuit policies enabling auditable autonomy. Nature Machine Intelligence. Springer Nature.https://doi.org/10.1038/s42256-020-00237-3 
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Lechner, M., Hasani, R., Rus, D., &; Grosu, R. (2020). Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 5446–5452). Paris, France: IEEE.https://doi.org/10.1109/ICRA40945.2020.9196608 
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Bogomolov, S., Forets, M., Frehse, G., Potomkin, K., &; Schilling, C. (2020). Reachability analysis of linear hybrid systems via block decomposition. In Proceedings of the International Conference on Embedded Software. Virtual .
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Henzinger, T. A., &; Sarac, N. E. (2020). Monitorability under assumptions. In Runtime Verification (Vol. 12399, pp. 3–18). Los Angeles, CA, United States: Springer Nature.https://doi.org/10.1007/978-3-030-60508-7_1 
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Kragl, B., Qadeer, S., &; Henzinger, T. A. (2020). Refinement for structured concurrent programs. In Computer Aided Verification (Vol. 12224, pp. 275–298). Springer Nature.https://doi.org/10.1007/978-3-030-53288-8_14 
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Kragl, B., Enea, C., Henzinger, T. A., Mutluergil, S. O., &; Qadeer, S. (2020). Inductive sequentialization of asynchronous programs. In Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation (pp. 227–242). London, United Kingdom: Association for Computing Machinery.https://doi.org/10.1145/3385412.3385980 
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Nickovic, D., Lebeltel, O., Maler, O., Ferrere, T., &; Ulus, D. (2020). AMT 2.0: Qualitative and quantitative trace analysis with extended signal temporal logic. International Journal on Software Tools for Technology Transfer. Springer Nature.https://doi.org/10.1007/s10009-020-00582-z 
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Kragl, B. (2020). Verifying concurrent programs: Refinement, synchronization, sequentialization. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:8332 
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Garcia Soto, M., &; Prabhakar, P. (2020). Hybridization for stability verification of nonlinear switched systems. In 2020 IEEE Real-Time Systems Symposium (pp. 244–256). Houston, TX, USA : IEEE.https://doi.org/10.1109/RTSS49844.2020.00031 
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Garcia Soto, M., &; Prabhakar, P. (2020). Abstraction based verification of stability of polyhedral switched systems. Nonlinear Analysis: Hybrid Systems. Elsevier.https://doi.org/10.1016/j.nahs.2020.100856 
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Kundu, A., Garcia Soto, M., &; Prabhakar, P. (2019). Formal synthesis of stabilizing controllers for periodically controlled linear switched systems. In 5th Indian Control Conference Proceedings. Delhi, India: IEEE.https://doi.org/10.1109/INDIANCC.2019.8715598 
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Avni, G., Henzinger, T. A., Ibsen-Jensen, R., &; Novotny, P. (2019). Bidding games on Markov decision processes. In https://doi.org/10.1007/978-3-030-30806-3_1__Proceedings of the 13th International Conference of Reachability Problems (Vol. 11674, pp. 1–12). Brussels, Belgium: Springer.https://doi.org/10.1007/978-3-030-30806-3_1 
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Lechner, M., Hasani, R., Zimmer, M., Henzinger, T. A., &; Grosu, R. (2019). Designing worm-inspired neural networks for interpretable robotic control. In Proceedings - IEEE International Conference on Robotics and Automation (Vol. 2019–May). Montreal, QC, Canada: IEEE.https://doi.org/10.1109/icra.2019.8793840 
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