1. Efficiently learning simple timed automata

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2008, Induction of Process Models (IPM 2008). Bridewell, W., Calders, T., de Medeiros, A. K., Kramer, S., Pechenizkiy, M. & Todorovski, L. (eds.). Antwerp: University of Antwerp, p. 61-68 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  2. Efficiently learning timed models from observations

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2008, Benelearn 2008. Wehenkel, L., Geurts, P. & Maree, R. (eds.). Luik: University of Liege, p. 75-76 2 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  3. Exact DFA Identification Using SAT Solvers

    Heule, MJH. & Verwer, SE., 2010, Grammatical Inference: Theoretical Results and Applications 10th International Colloquium, ICGI 2010. Sempere, JM. & García, P. (eds.). Berlin: Springer, p. 66-79 14 p. (Lecture Notes in Computer Science; vol. 6339).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  4. Flexible State-Merging for learning (P)DFAs in Python

    Hammerschmidt, C., Loos, B., State, R., Engel, T. & Verwer, S., 2016, Proceedings of The 13th International Conference on Grammatical Inference: The JMLR Workshop and Conference, The Sequence PredictIction ChallengE (SPiCe). Verwer, S., van Zaanen, M. & Smetsers, R. (eds.). JMLR, Vol. 57. p. 154-159 6 p. (JMLR: Workshop and Conference Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  5. Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms

    Hammerschmidt, C. A., State, R. & Verwer, S., 2017, ArXiv Preprint. Vol. abs/1707.09430.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientific

  6. Identifying an automaton model for timed data

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2006, Proceedings of the Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn). Saeys, Y., Tsiporkova, E., Baets, B. D. & van de Peer, Y. (eds.). Benelearn, p. 57-64 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  7. Identifying an automaton model for timed data (extended abstract)

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2006, Proceedings of the Belgium-Dutch Conference on Artificial Intelligence (BNAIC). Schobbens, P-Y., Vanhoof, W. & Schwanen, G. (eds.). BNVKI, p. 439-440 2 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  8. Improved privacy of dynamic group services

    Veugen, T., Doumen, J., Erkin, Z., Pellegrino, N., Verwer, S. & Weber, J., 2017, In : Eurasip Journal on Information Security. 2017, 1, p. 1-9 9 p., 3.

    Research output: Contribution to journalArticleScientificpeer-review

  9. Improving active Mealy machine learning for protocol conformance testing

    Aarts, F., Kuppens, H., Tretmans, J., Vaandrager, FW. & Verwer, SE., 2014, In : Machine Learning. 96, 1-2, p. 189-224 36 p.

    Research output: Contribution to journalArticleScientificpeer-review

  10. Lane-Change Intention Estimation for Car-Following Control in Autonomous Driving

    Zhang, Y., Lin, Q., Wang, J., Verwer, S. & Dolan, J. M., 2018, In : IEEE Transactions on Intelligent Vehicles. 3, 3, p. 276-286 11 p.

    Research output: Contribution to journalArticleScientificpeer-review

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