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Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text, , , , , и . Statistical Relational Artificial Intelligence, Papers from the 2013 AAAI Workshop, Bellevue, Washington, USA, July 15, 2013, том WS-13-16 из AAAI Workshops, AAAI, (2013)Statistical Relational Artificial Intelligence: Logic, Probability, and Computation, , , и . Synthesis Lectures on Artificial Intelligence and Machine Learning Morgan & Claypool, San Rafael, CA, (2016)Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models, , , , , , и . Proceedings of ECML, (2010)Statistical Relational Artificial Intelligence: Logic, Probability, and Computation, , , и . Synthesis Lectures on Artificial Intelligence and Machine Learning Morgan & Claypool Publishers, (2016)Effectively creating weakly labeled training examples via approximate domain knowledge, , , , , и . Inductive Logic Programming, Springer, (2015)Graph Enhanced Memory Networks for Sentiment Analysis., , и . ECML/PKDD (1), том 10534 из Lecture Notes in Computer Science, стр. 374-389. Springer, (2017)Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures., , , , , , и . CoRR, (2019)Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models., , , и . Pacific Symposium on Biocomputing, стр. 192-203. (2003)Equitable Partitions of Concave Free Energies., и . UAI, стр. 602-611. AUAI Press, (2015)Structured Object-Aware Physics Prediction for Video Modeling and Planning., , , , и . ICLR, OpenReview.net, (2020)