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Abstract: Whereas acausal Bayesian networks represent probabilistic independence, causal Bayesian networks represent causal relationships. In this paper, we examine Bayesian methods for learning both types of networks. Bayesian methods for learning acausal networks are fairly well developed. These methods often employ assumptions to facilitate the construction of priors, including the assumptions of parameter independence, parameter modularity, and likelihood equivalence. We show that although these... (Update)
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BibTeX entry: (Update)
D. Heckerman, "A Bayesian approach to learning causal networks ", In Besnard and Hanks [158]. http://citeseer.ist.psu.edu/heckerman95bayesian.html More
@techreport{ david95bayesian,
author = "Heckerman, David",
title = "{A} {B}ayesian {A}pproach to {L}earning {C}ausal {N}etworks",
number = "MSR-TR-95-04",
month = "March",
year = "1995",
url = "citeseer.ist.psu.edu/heckerman95bayesian.html" }
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351 Learning Bayesian networks: The combination of knowledge and.. - Heckerman, Geiger et al. - 1995
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166 Evaluating influence diagrams (context) - Shachter - 1986
148 Bayesian analysis in expert systems (context) - Spiegelhalter, Dawid et al. - 1993
130 Influence diagrams (context) - Howard, Matheson - 1981
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119 Operations for learning with graphical models - Buntine - 1994
118 Sequential updating of conditional probabilities on directed.. (context) - Spiegelhalter, Lauritzen - 1990
104 A theory of inferred causation - Pearl, Verma - 1991
86 Springer-Verlag (context) - Spirtes, Glymour et al. - 1993
84 Theory refinement on Bayesian networks - Buntine - 1991
72 Equivalence and synthesis of causal models (context) - Verma, Pearl - 1990
58 Causal diagrams for empirical research - Pearl
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11 Updating a diagnostic system using unconfirmed cases (context) - Titterington - 1976
11 Counterfactual dependence and time's arrow (context) - Lewis - 1978
5 Bayesian methods for the analysis of misclassified or incomp.. (context) - York - 1992
2 Personal communication (context) - Pearl
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