Factorisation of Probability Trees and its Application to Inference in Bayesian Networks.
Irene Martínez, Serafı́n Moral, Carmelo Rodríguez, Antonio Salmerón · Probabilistic Graphical Models · 2002
Bayesian networks can be seen as a factorisation of a joint probability distribution over a set of variables, based on the conditional independence relations amongst the variables. In this paper we show how it is possible to achieve a finer factorisation decomposing the origninal factors in which some conditions hold. The new ideas can be applied to algorithms able to deal wih factorised probabilistic potentials, as Lazy Propagation, LazyPenniless as well as Monte Carlo methods based on Importance Sampling.