Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
A successful interpretation of data goes through discovering crucial relationships between variables. Such a task can be accomplished by a Bayesian network. The dark side is that, ...
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
A complete diagnostic Bayesian network model cannot be achieved and the result of the constructed model cannot be guaranteed unless correct and reliable data are provided to the m...