4.5k citations · 5.7k across the 23 of their papers we have counts for
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cs.LG2021★ 10 cited
Likelihoods and Parameter Priors for Bayesian Networks
David Heckerman, Dan Geiger
We develop simple methods for constructing likelihoods and parameter priors for learning about the parameters and structure of a Bayesian network. In particular, we introduce sever…
stat.ML2021★ 102 cited
Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions
Dan Geiger, David Heckerman
We develop simple methods for constructing parameter priors for model choice among Directed Acyclic Graphical (DAG) models. In particular, we introduce several assumptions that per…