50 Jahre Uni Lübeck

M.Sc. Marcel Wienöbst

Forschung


Forschungsinteressen

Veröffentlichungen

2022

  • Benito van der Zander, Marcel Wienöbst, Markus Bläser, Maciej Liskiewicz:
    Identification in Tree-shaped Linear Structural Causal Models.
    In Proceedings of The 25th International Conference on Artificial Intelligence and Statistics, S. 6770-6792. PLMR, 2022.
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2021

  • Marcel Wienöbst, Maciej Liskiewicz:
    An Approach to Reduce the Number of Conditional Independence Tests in the PC Algorithm.
    In Proceeding of 44th German Conference on AI (KI 2021), Band 12873 von Lecture Notes in Computer Science, S. 276-288. Springer, 2021.
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  • Marcel Wienöbst, Max Bannach, Maciej Liskiewicz:
    Extendability of Causal Graphical Models: Algorithms and Computational Complexity.
    In Proc. of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence (UAI 2021), Band 161 von Communications in Computer and Information Science, S. 1248-1257. PMLR, 2021.
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  • Marcel Wienöbst, Max Bannach, Maciej Liskiewicz:
    Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs.
    In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI'21), S. 12198-12206. AAAI Press, 2021.
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  • Marcel Wienöbst, Max Bannach, Maciej Liskiewicz:
    Recent Advances in Counting and Sampling Markov Equivalent DAGs.
    In Proceeding of 44th German Conference on AI (KI 2021), Band 12873 von Lecture Notes in Computer Science, S. 271-275. Springer, 2021.
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2020

  • Max Bannach, Sebastian Berndt, Martin Schuster, Marcel Wienöbst:
    PACE Solver Description: PID*.
    In Proceedings of the 15th International Symposium on Parameterized and Exact Computation (IPEC 2020), LIPIcs, 2020.
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  • Max Bannach, Sebastian Berndt, Martin Schuster, Marcel Wienöbst:
    PACE Solver Description: Fluid.
    In Proceedings of the 15th International Symposium on Parameterized and Exact Computation (IPEC 2020), LIPIcs, 2020.
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  • Marcel Wienöbst, Maciej Liskiewicz:
    Recovering Causal Structures from Low-Order Conditional Independencies.
    In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI'20), New York, New York USA, S. 10302-10309. AAAI Press, 2020.
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2019

  • Marcel Wienöbst:
    Constraint-based causal structure learning exploiting low-order conditional independences.
    Universität zu Lübeck, Institut für Theoretische Informatik, 2019.
    Gutachter: Maciej Liskiewicz, Ralf Möller.
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2016

  • Marcel Wienöbst:
    Experimentelle Analyse von Algorithmen zur Lösung des Bisektionsproblems in Graphen.
    Universität zu Lübeck, Institut für Theoretische Informatik, 2016.
    Gutachter: Maciej Liskiewicz, Hanns-Martin Teichert.
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