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A Bayesian Approach for Estimating Causal Effects from Observational Data.

, , , and . AAAI, page 5395-5402. AAAI Press, (2020)

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DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulation., , and . CoRR, (2022)Context-Specific and Local Independence in Markovian Dependence Structures., , and . Dependence Logic, Springer, (2016)A logical approach to context-specific independence., , , , and . Ann. Pure Appl. Log., 170 (9): 975-992 (2019)High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study., , , , , and . Comput. Stat. Data Anal., (2020)Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood., , , and . CoRR, (2016)Learning pairwise Markov network structures using correlation neighborhoods., , and . CoRR, (2019)The role of local partial independence in learning of Bayesian networks., , , and . Int. J. Approx. Reason., (2016)Uncertainty quantification in automated valuation models with locally weighted conformal prediction., , , and . CoRR, (2023)Structure Learning for Bayesian Networks over Labeled DAGs., , , and . PGM, volume 72 of Proceedings of Machine Learning Research, page 133-144. PMLR, (2018)Learning Chordal Markov Networks by Constraint Satisfaction., , , , and . NIPS, page 1349-1357. (2013)