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Learning to play the Chess Variant Crazyhouse above World Champion Level with Deep Neural Networks and Human Data., , , , and . CoRR, (2019)Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks, , and . (2019)cite arxiv:1907.06732Comment: 12 Pages, 6 Figures.Equitable Partitions of Concave Free Energies., and . UAI, page 602-611. AUAI Press, (2015)Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models., , , and . Pacific Symposium on Biocomputing, page 192-203. (2003)Statistical Relational Artificial Intelligence: Logic, Probability, and Computation, , , and . Synthesis Lectures on Artificial Intelligence and Machine Learning Morgan & Claypool Publishers, (2016)Effectively creating weakly labeled training examples via approximate domain knowledge, , , , , and . Inductive Logic Programming, Springer, (2015)Statistical Relational Learning., and . Encyclopedia of Machine Learning and Data Mining, Springer, (2017)Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text, , , , , and . Statistical Relational Artificial Intelligence, Papers from the 2013 AAAI Workshop, Bellevue, Washington, USA, July 15, 2013, volume WS-13-16 of AAAI Workshops, AAAI, (2013)Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models, , , , , , and . Proceedings of ECML, (2010)A Revised Publication Model for ECML PKDD, , , and . CoRR, (2012)