The class of graphical models is a family of probability distributions for which conditional dependencies can be read off from a graph. If the graph is decomposable, the maximum likelihood estimates of the parameters in the model can be shown to be on exact form. This is what enables ESS to be fast and efficient for model selection in decomposable graphical models.
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