I get stuck on this problem. If in a Bayesian network, how can we do tensor multiplication on the conditional probability table so that it eventually gives the joint probability distribution? If a node has K parents, then the CPT of this node will be of K+1 dimension, where the first dimension is for itself and other dimensions are for its parents whose order is the default output of node.ancestor(). Is there an algorithm for this? Thanks in advance!