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A Bayesian Approach for Estimating Causal Effects from Observational Data., , , и . AAAI, стр. 5395-5402. AAAI Press, (2020)Learning Bayesian Networks with Cops and Robbers., и . PGM, том 138 из Proceedings of Machine Learning Research, стр. 473-484. PMLR, (2020)Counting and Sampling Directed Acyclic Graphs for Learning Bayesian Networks.. University of Helsinki, Finland, (2019)base-search.net (ftunivhelsihelda:oai:helda.helsinki.fi:10138/306782).Finding Optimal Bayesian Networks with Local Structure., , и . PGM, том 72 из Proceedings of Machine Learning Research, стр. 451-462. PMLR, (2018)Counting and Sampling Markov Equivalent Directed Acyclic Graphs., и . AAAI, стр. 7984-7991. AAAI Press, (2019)Visualizing Quickest Visibility Maps.. SoCG, том 34 из LIPIcs, стр. 26-28. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2015)The Mixing of Markov Chains on Linear Extensions in Practice., , и . IJCAI, стр. 524-530. ijcai.org, (2017)Learning Bayesian networks with local structure, mixed variables, and exact algorithms., , и . Int. J. Approx. Reason., (2019)Shortest path to a segment and quickest visibility queries., , , , , , , и . J. Comput. Geom., 7 (2): 77-100 (2016)An Efficient Algorithm for Counting Markov Equivalent DAGs., , и . AAAI, стр. 10136-10143. AAAI Press, (2020)