article Open AccessTop 1% cited
Learning Bayesian networks: The combination of knowledge and statistical data
Machine Learning · 1995 · Vol. 20(3) · pp. 197–243
David Heckerman✉(Microsoft (United States))Dan Geiger(Microsoft (United States))David M. Chickering(Microsoft (United States))
Bayesian Modeling and Causal InferenceData Quality and ManagementAI-based Problem Solving and PlanningPrior probabilityComputer scienceBayesian networkArtificial intelligenceMachine learningVariable-order Bayesian networkEquivalence (formal languages)Bayesian probabilityConditional independenceData mining
Citations
2,034
FWCI
34.68
field-weighted impact
References
64
Percentile
100%
vs. same field & year
Citations per year
Cited by
Bayesian Network Classifiers
Machine Learning · 1997 · 4,702 citations
Advantages and challenges of Bayesian networks in environmental modelling
Ecological Modelling · 2007 · 1,086 citations
Link prediction in complex networks: A survey
Physica A Statistical Mechanics and its Applications · 2010 · 2,795 citations
Markov logic networks
Machine Learning · 2006 · 2,661 citations
The max-min hill-climbing Bayesian network structure learning algorithm
Machine Learning · 2006 · 1,797 citations
References
A Bayesian Method for the Induction of Probabilistic Networks from Data
Machine Learning · 1992 · 3,490 citations
Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1977 · 49,286 citations
Equation of State Calculations by Fast Computing Machines
The Journal of Chemical Physics · 1953 · 36,613 citations
Approximating discrete probability distributions with dependence trees
IEEE Transactions on Information Theory · 1968 · 2,618 citations
Lectures on Functional Equations and their Applications.
American Mathematical Monthly · 1968 · 2,621 citations
A Bayesian method for the induction of probabilistic networks from data
Machine Learning · 1992 · 2,337 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.