Marco Wilhelm

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Marco Wilhelm is a research assistant at the Department of Statistics at TU Dortmund University and a PhD student at the Department of Computer Science at the same university working in the field of knowledge representation and reasoning. His main research interest is in probabilistic inference based on the principle of maximum entropy. He participated in the DFG Research Unit 1513 on Hybrid Reasoning for Intelligent Systems from 2015 to 2019 and finished his mathematics studies at TU Dortmund University with a Diploma degree in 2012. Marco Wilhelm is responsible for the research data management of FAIR.
Wilhelm, M., Howey, D., Kern-Isberner, G., Sauerwald, K., & Beierle C. (2021). Conditional Inference and Activation of Knowledge Entities in ACT-R. arXiv:2110.15214 [cs.AI]. https://doi.org/10.48550/arXiv.2110.15214
Wilhelm, M., & Kern-Isberner G. (2021). Focused Inference and System P. Proceedings of the 35th Conference on Artificial Intelligence (AAAI). https://ojs.aaai.org/index.php/AAAI/article/view/16808
Wilhelm, M. &, Kern-Isberner, G., Finthammer, M., & Beierle C. (2019). Integrating Typed Model Counting into First-Order Maximum Entropy Computations and the Connection to Markov Logic Networks. Proceedings of the 32nd International Florida Artificial Intelligence Research Society Conference (FLAIRS). https://aaai.org/ocs/index.php/FLAIRS/FLAIRS19/paper/view/18235
Wilhelm, M., Kern-Isberner, G., Ecke, A., & Baader, F. (2019). Counting Strategies for the Probabilistic Description Logic ALC^ME Under the Principle of Maximum Entropy. Proceedings of the 16th Edition of the European Conference on Logics in Artificial Intelligence (JELIA). https://doi.org/10.1007/978-3-030-19570-0_28