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math.ST2020
Learning Bayesian Networks from Incomplete Data with the Node-Average Likelihood
Tjebbe Bodewes, Marco Scutari
Bayesian network (BN) structure learning from complete data has been extensively studied in the literature. However, fewer theoretical results are available for incomplete data, an…
math.ST2017
Dirichlet Bayesian Network Scores and the Maximum Relative Entropy Principle
Marco Scutari
A classic approach for learning Bayesian networks from data is to identify a maximum a posteriori (MAP) network structure. In the case of discrete Bayesian networks, MAP networks a…
math.ST2012
On the Prior and Posterior Distributions Used in Graphical Modelling
Marco Scutari
Graphical model learning and inference are often performed using Bayesian techniques. In particular, learning is usually performed in two separate steps. First, the graph structure…