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Effectively creating weakly labeled training examples via approximate domain knowledge, , , , , and . Inductive Logic Programming, Springer, (2015)Kernelized Map Matching for noisy trajectories, and . Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen & Adaptivitaet, Kassel, Germany, (2010)Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models, , , , , , and . Proceedings of ECML, (2010)Statistical Relational Artificial Intelligence: Logic, Probability, and Computation, , , and . Synthesis Lectures on Artificial Intelligence and Machine Learning Morgan & Claypool Publishers, (2016)Statistical Relational Artificial Intelligence: Logic, Probability, and Computation, , , and . Synthesis Lectures on Artificial Intelligence and Machine Learning Morgan & Claypool, San Rafael, CA, (2016)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)Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures., , , , , , and . CoRR, (2019)Faster Attend-Infer-Repeat with Tractable Probabilistic Models., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5966-5975. PMLR, (2019)Graph Enhanced Memory Networks for Sentiment Analysis., , and . ECML/PKDD (1), volume 10534 of Lecture Notes in Computer Science, page 374-389. Springer, (2017)Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks, , and . (2019)cite arxiv:1907.06732Comment: 12 Pages, 6 Figures.