Advanced Inference in Bayesian Networks

The previous chapter introduced inference in discrete variable Bayesian networks. This used evidence propagation on the junction tree to find marginal distributions of interest. This chapter presents a tutorial introduction to some of the various types of calculations which can also be performed with the junction tree, specifically: Sampling. Most likely configurations. Fast retraction. Gaussian and conditional Gaussian models.

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