On Bayesian Network Inference with Simple Propagation

Simple Propagation (SP) was recently proposed as a new join tree propagation algorithm for exact inference in discrete Bayesian networks and empirically shown to be faster than Lazy Propagation (LP) when applied on optimal (or close to) join trees built from real-world and benchmark Bayesian networks. This paper extends SP in two directions. First, we propose and empirically evaluate eight heuristics for determining elimination orderings in SP. Second, we show that the relevant potentials in SP are precisely those in LP.