  Bayesian network is a complete model for the variables and their
relationships, it can be used to answer probabilistic queries about them. A
Bayesian network can thus be considered a mechanism for automatically applying
Bayes' theorem to complex problems. In the application of Bayesian networks,
most of the work is related to probabilistic inferences. Any variable updating
in any node of Bayesian networks might result in the evidence propagation
across the Bayesian networks. This paper sums up various inference techniques
in Bayesian networks and provide guidance for the algorithm calculation in
probabilistic inference in Bayesian networks.
