Factorisation of Probability Trees and its Applications
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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 hols. The new ideas can be applied to algorithms able to deal wih factorised probabilistic potentials, as Lazy Propagation, Lazy-Penniless and Importance Sampling.