Publikace

• 2023

  ANDRIUSHCHENKO, R.; BARTOCCI, E.; ČEŠKA, M.; FRANCESCO, P.; SARAH, S. Deductive Controller Synthesis for Probabilistic Hyperproperties. In Quantitative Evaluation of SysTems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Cham: Springer Verlag, 2023. s. 288-306. ISBN: 978-3-031-43834-9.
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  ANDRIUSHCHENKO, R.; ALEXANDER, B.; ČEŠKA, M.; JUNGES, S.; KATOEN, J.; MACÁK, F. Search and Explore: Symbiotic Policy Synthesis in POMDPs. In Computer Aided Verification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Cham: Springer Verlag, 2023. s. 113-135. ISBN: 978-3-031-37708-2.
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• 2022

  HELFRICH, M.; ČEŠKA, M.; KŘETÍNSKÝ, J.; MARTIČEK, Š. Abstraction-Based Segmental Simulation of Chemical Reaction Networks. In International Conference on Computational Methods in Systems Biology. Lecture Notes in Bioinformatics. Bucharest: Springer Verlag, 2022. s. 41-60. ISBN: 978-3-031-15033-3.
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  ANDRIUSHCHENKO, R.; ČEŠKA, M.; MARCIN, V.; VOJNAR, T. GPU-Accelerated Synthesis of Probabilistic Programs. In International Conference on Computer Aided Systems Theory (EUROCAST'22). Lecture Notes in Computer Science. Cham: 2022. s. 256-266. ISBN: 978-3-031-25312-6.
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  ČEŠKA, M.; MATYÁŠ, J.; MRÁZEK, V.; SEKANINA, L.; VAŠÍČEK, Z.; VOJNAR, T. SagTree: Towards Efficient Mutation in Evolutionary Circuit Approximation. Swarm and Evolutionary Computation, 2022, roč. 69, č. 100986, s. 1-10. ISSN: 2210-6502.
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  ČEŠKA, M.; MATYÁŠ, J.; MRÁZEK, V.; VOJNAR, T. Designing Approximate Arithmetic Circuits with Combined Error Constraints. In Proceeding of 25th Euromicro Conference on Digital System Design 2022 (DSD'22). Gran Canaria: Institute of Electrical and Electronics Engineers, 2022. s. 785-792. ISBN: 978-1-6654-7404-7.
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  ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; KATOEN, J. Inductive Synthesis of Finite-State Controllers for POMDPs. In Conference on Uncertainty in Artificial Intelligence. Proceedings of Machine Learning Research. Eindhoven: Proceedings of Machine Learning Research, 2022. s. 85-95. ISSN: 2640-3498.
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• 2021

  ČEŠKA, M.; JUNGES, S.; KATOEN, J.; HENSE, C. Counterexample-guided inductive synthesis for probabilistic systems. Formal Aspects of Computing, 2021, roč. 33, č. 4, s. 637-667. ISSN: 0934-5043.
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  ANDRIUSHCHENKO, R.; ČEŠKA, M.; STUPINSKÝ, Š.; JUNGES, S.; KATOEN, J. PAYNT: A Tool for Inductive Synthesis of Probabilistic Programs. In International Conference on Computer Aided Verification (CAV). Lecture Notes in Computer Science. Cham: Springer Verlag, 2021. s. 856-869. ISBN: 978-3-030-81684-1.
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  ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; KATOEN, J. Inductive Synthesis for Probabilistic Programs Reaches New Horizons. International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS). Lecture Notes in Computer Science. Cham: Springer International Publishing, 2021. s. 191-209. ISBN: 978-3-030-72015-5.
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  ANDRIUSHCHENKO, R.; ČEŠKA, M.; ABATE, A.; KWIATKOWSKA, M. Adaptive formal approximations of Markov chains. PERFORMANCE EVALUATION, 2021, roč. 148, č. 102207, s. 1-23. ISSN: 0166-5316.
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• 2020

  ČEŠKA, M. Towards Computer-Aided Quantitative Synthesis. Brno: Faculty of Information Technology BUT, 2020. s. 0-0.
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  ČEŠKA, M.; MATYÁŠ, J.; MRÁZEK, V.; SEKANINA, L.; VAŠÍČEK, Z.; VOJNAR, T. Adaptive verifiability-driven strategy for evolutionary approximation of arithmetic circuits. APPLIED SOFT COMPUTING, 2020, roč. 95, č. 106466, s. 1-17. ISSN: 1568-4946.
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  ČEŠKA, M.; MATYÁŠ, J.; MRÁZEK, V.; VOJNAR, T. Satisfiability Solving Meets Evolutionary Optimisation in Designing Approximate Circuits. In Theory and Applications of Satisfiability Testing - SAT 2020. Lecture Notes in Computer Science. Alghero: Springer International Publishing, 2020. s. 481-491. ISBN: 978-3-030-51824-0.
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  ČEŠKA, M.; CHAU, C.; KŘETÍNSKÝ, J. SeQuaiA: A Scalable Tool for Semi-Quantitative Analysis of Chemical Reaction Networks. In International Conference on Computer Aided Verification. Lecture Notes in Computer Science. Cham: Springer Verlag, 2020. s. 653-666. ISBN: 978-3-030-53287-1.
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  MATYÁŠ, J.; PANKUCH, A.; VOJNAR, T.; ČEŠKA, M.; ČEŠKA, M. Approximating Complex Arithmetic Circuits with Guaranteed Worst-Case Relative Error. In International Conference on Computer Aided Systems Theory (EUROCAST'19). Lecture Notes in Computer Science. Cham: Springer Verlag, 2020. s. 482-490. ISBN: 978-3-030-45092-2.
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  ČEŠKA, M.; HAVLENA, V.; HOLÍK, L.; LENGÁL, O.; VOJNAR, T. Approximate Reduction of Finite Automata for High-Speed Network Intrusion Detection. International Journal on Software Tools for Technology Transfer, 2020, roč. 22, č. 5, s. 523-539. ISSN: 1433-2779.
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• 2019

  ČEŠKA, M.; HENSE, C.; JANSEN, N.; JUNGES, S.; KATOEN, J. Model Repair Revamped - On the Automated Synthesis of Markov Chains -. In From Reactive Systems to Cyber-Physical Systems. Lecture Notes of Computer Science. Cham: Springer International Publishing, 2019. s. 107-125. ISBN: 978-3-030-31513-9.
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  ČEŠKA, M.; JANSEN, N.; JUNGES, S.; KATOEN, J. Shepherding Hordes of Markov Chains. In Proceedings of 25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems. Lecture Notes in Computer Science. Praha: Springer International Publishing, 2019. s. 172-190. ISBN: 978-3-030-17464-4.
  Detail | WWW | Plný text v Digitální knihovně

  ČEŠKA, M.; KŘETÍNSKÝ, J. Semi-Quantitative Abstraction and Analysis of Chemical Reaction Networks. In Proceedings of the 31th International Conference on Computer Aided Verification (CAV'19). Lecture Notes of Computer Science. New York: Springer International Publishing, 2019. s. 475-496. ISBN: 978-3-030-25540-4.
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  ČEŠKA, M.; KŘETÍNSKÝ, J. Semi-quantitative Abstraction and Analysis of Chemical Reaction Networks (Extended Abstract). In Proceedings of the 17th International Conference on Computational Methods in Systems Biology. Lecture Notes in Bioinformatics. Trieste: Springer International Publishing, 2019. s. 337-341. ISBN: 978-3-030-31303-6.
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  HAVLENA, V.; ČEŠKA, M.; HOLÍK, L.; KOŘENEK, J.; LENGÁL, O.; MATOUŠEK, D.; MATOUŠEK, J.; SEMRIČ, J.; VOJNAR, T. Deep Packet Inspection in FPGAs via Approximate Nondeterministic Automata. In Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. San Diego, CA: Institute of Electrical and Electronics Engineers, 2019. s. 109-117. ISBN: 978-1-7281-1131-5.
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  ČEŠKA, M.; HENSE, C.; JUNGES, S.; KATOEN, J. Counterexample-Driven Synthesis for Probabilistic Program Sketches. In Proceedings of the 23rd International Symposium on Formal Methods. Lecture Notes of Computer Science. Porto: Springer International Publishing, 2019. s. 101-120. ISBN: 978-3-030-30941-1.
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• 2018

  ČEŠKA, M.; MATYÁŠ, J.; MRÁZEK, V.; VAŠÍČEK, Z.; SEKANINA, L.; VOJNAR, T. ADAC: Automated Design of Approximate Circuits. In Proceedings of 30th International Conference on Computer Aided Verification (CAV'18). Oxford, UK: Springer International Publishing, 2018. s. 612-620. ISBN: 978-3-319-96145-3.
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  CALINESCU, R.; ČEŠKA, M.; GERASIMOU, S.; KWIATKOWSKA, M.; PAOLETTI, N. Efficient Synthesis of Robust Models for Stochastic Systems. JOURNAL OF SYSTEMS AND SOFTWARE, 2018, roč. 2018, č. 143, s. 140-158. ISSN: 0164-1212.
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  ČEŠKA, M.; HAVLENA, V.; HOLÍK, L.; LENGÁL, O.; VOJNAR, T. Approximate Reduction of Finite Automata for High-Speed Network Intrusion Detection. In Proceedings of TACAS'18. Lecture Notes in Computer Science. Thessaloniki: Springer Verlag, 2018. s. 155-175. ISSN: 0302-9743.
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• 2017

  ČEŠKA, M.; CALINESCU, R.; GERASIMOU, S.; KWIATKOWSKA, M.; PAOLETTI, N. Designing Robust Software Systems through Parametric Markov Chain Synthesis. In Proceedings of 14th IEEE International Conference On Software Architecture. New Jersey: IEEE Computer Society, 2017. s. 131-140. ISBN: 978-1-5090-5729-0.
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  LAURENTI, L.; ABATE, A.; BORTOLUSSI, L.; CARDELLI, L.; ČEŠKA, M.; KWIATKOWSKA, M. Reachability Computation for Switching Diffusions:Finite Abstractions with Certifiable and Tuneable Precision. In Proceedings of the 20th ACM International Conference on Hybrid Systems: Computation and Control. ACM. New York: Association for Computing Machinery, 2017. s. 55-64. ISBN: 978-1-4503-4590-3.
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  ČEŠKA, M.; MATYÁŠ, J.; MRÁZEK, V.; VAŠÍČEK, Z.; SEKANINA, L.; VOJNAR, T. Approximating Complex Arithmetic Circuits with Formal Error Guarantees: 32-bit Multipliers Accomplished. In Proceedings of 36th IEEE/ACM International Conference On Computer Aided Design (ICCAD). Irvine, CA: Institute of Electrical and Electronics Engineers, 2017. s. 416-423. ISBN: 978-1-5386-3093-8.
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  ČEŠKA, M.; ČEŠKA, M.; PAOLETTI, N. Precise Parameter Synthesis for Stochastic Petri Nets with Interval Rate Parameters. In Proceedings of 16th International Conference on Computer Aided Systems Theory. LNCS volume 10672. Heidelberg: Springer Verlag, 2017. s. 38-46. ISBN: 978-3-319-74726-2.
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  ČEŠKA, M.; CALINESCU, R.; GERASIMOU, S.; KWIATKOWSKA, M.; PAOLETTI, N. Recent Advances in Designing Robust Probabilistic Systems. 2nd International Workshop on Design and Analysis of Robust Systems (Extended Abstract). Berlin: 2017. s. 1-3.
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  ČEŠKA, M.; CARDELLI, L.; FRANZLE, M.; KWIATKOWSKA, M.; LAURENTI, L.; PAOLETTI, N.; WHITBY, M. Syntax-Guided Optimal Synthesis for Chemical Reaction Networks. In Proceedings of the 29th International Conference on Computer Aided Verification. Lecture Notes in Computer Science. Heidelberg: Springer Verlag, 2017. s. 375-395. ISBN: 978-3-319-63390-9.
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  ČEŠKA, M.; CALINESCU, R.; GERASIMOU, S.; KWIATKOWSKA, M.; PAOLETTI, N. RODES: A Robust-Design Synthesis Tool for Probabilistic Systems. In Proceedings of 14th International Conference on Quantitative Evaluation of SysTems. Heidelberg: Springer Verlag, 2017. s. 304-308. ISBN: 978-3-319-66335-7.
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• 2016

  ČEŠKA, M.; DANNENBERG, F.; KWIATKOWSKA, M.; PAOLETTI, N.; BRIM, L. Precise parameter synthesis for stochastic biochemical systems. Acta Informatica, 2016, roč. 54, č. 6, s. 589-623. ISSN: 0001-5903.
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  ABATE, A.; ČEŠKA, M.; KWIATKOWSKA, M. Approximate Policy Iteration for Markov Decision Processes via Quantitative Adaptive Aggregations. In Proceedings of 14th International Symposium on Automated Technology for Verification and Analysis. Lecture Notes in Computer Science. Heidelberg: Springer Verlag, 2016. s. 13-31. ISBN: 978-3-319-46519-7.
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  ČEŠKA, M.; ALDEGHERI, S.; BARNAT, J.; BOMBIERI, N.; BUSATO, F. Parametric Multi-Step Scheme for GPU-Accelerated Graph Decomposition into Strongly Connected Components. In Proceedings of 2nd Workshop on Performance Engineering for Large Scale Graph Analytics. Lecture Notes in Computer Science. Cham: Springer Verlag, 2016. s. 519-531. ISBN: 978-3-319-58942-8.
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  ČEŠKA, M.; PILAŘ, P.; PAOLETTI, N.; BRIM, L.; KWIATKOWSKA, M. PRISM-PSY: Precise GPU-Accelerated Parameter Synthesis for Stochastic Systems. In Proceedings of the 22nd International Conference on Tools and Algorithms for the Construction and Analysis of Systems. Lecture Notes in Computer Science. Lecture Notes in Computer Science. Berlin: Springer International Publishing, 2016. s. 367-384. ISBN: 978-3-662-49673-2. ISSN: 0302-9743.
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