Mastering Probabilistic Graphical Models Using Python

MAP using belief propagation

In the previous section, we discussed the MAP variable elimination algorithm. In the same way that we extended the sum-product variable elimination algorithm for the clique tree and ended up on the belief propagation algorithm, we can perform MAP using the belief propagation. In cases where variable elimination can be computationally intractable, belief propagation has a clear advantage.

The procedure for belief propagation remains the same as discussed in the case of the sum-product. The only thing that changes is the message that is passed between the two clusters and . Earlier, we used to compute messages from to ...