Making an inference with cyclic networks is not straightforward. Belief propagation may still be used, but it could yield incorrect inferences. Generalised belief propagation was proposed as an improvement over belief propagation. I walk through the generalised belief propagation with an example in this post.

Belief propagation, also known as sum-product algorithm, is an inference framework. In the context of Bayesian networks, this algorithm is often used to compute the marginal probability distribution. In this post, I walk through the computations involved in the belief propagation.

In this post, I consider joint probability of discrete random variables as tensors.