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Building Blocks for Variational Bayesian Learning of Latent Variable Models

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Figure 1: The dash-lined nodes and connections can be ignored while updating the shadowed node.Left: In general, the whole Markov blanket needs to be considered
Figure 2: First subfigure from the left: The circle represents a Gaussian node corresponding tothe latent variable s conditioned by mean m and variance exp(−v)
Table 1: The forward messages or expectations that are provided by the output of different typesof nodes
Table 2: The backward messages or the gradients of the cost function w.r.t. certain expectations.The numbers in parentheses refer to defining equations
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