Temporally invariant Junction Tree for Inference in Dynamic Bayesian Network

摘要

Dynamic Bayesian networks (DBNs) extend Bayesian networks from static domains to dynamic domains. The only known generic method for exact inference in DBMs is based on dynamic expansion nad reduction of active slices. It is effective when the domain evolves relatively slowly, but is reported to be "too expensive" for fast evolving domain where inference is under time pressure.