Confident Bayesian Learning of Graphical Models

Confident Bayesian learning amounts to computing summaries of a posterior distribution either exactly or with probabilistic accuracy guarantees.

 I will review what is currently known about confident Bayesian structure learning in graphical models, focusing on the class of Bayesian networks and its subclass of chordal Markov networks