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Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood., , , and . CoRR, (2016)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)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)A Logical Approach to Context-Specific Independence., , , , and . WoLLIC, volume 9803 of Lecture Notes in Computer Science, page 165-182. Springer, (2016)A Bayesian Approach for Estimating Causal Effects from Observational Data., , , and . AAAI, page 5395-5402. AAAI Press, (2020)Representing local structure in Bayesian networks by Boolean functions., , and . Pattern Recognit. Lett., (2017)Marginal and simultaneous predictive classification using stratified graphical models., , , and . Adv. Data Anal. Classif., 10 (3): 305-326 (2016)Towards Scalable Bayesian Learning of Causal DAGs., , , and . NeurIPS, (2020)