Bayesian networks have been successfully applied to various tasks for probabilistic
reasoning and causal modeling. One major challenge in the application of Bayesian …

Abnormalities in modern process industries are reported by alarms. Strong inter-
connectivities within different units of a plant lead to annunciations of multiple alarms in a …

Bayesian networks (BNs) have been widely used in causal analysis because they can
express the statistical relationship between significant variables. To gain superior causal …

Latent dependency forest models (LDFMs) are a new type of probabilistic models with
dynamic dependency structures over random variables. They distinguish themselves from …

BELIEF CHANGE IN PROBABILISTIC KNOWLEDGE REPRESENTATIONS FOR OPEN AND
DYNAMIC COMPUTING ENVIRONMENTS A Thesis Submitted to the F Page 1 BELIEF …

Latent dependence forest models (LDFM) are a new type of probabilistic models with the
advantage of not requiring the difficult procedure of structure learning in model learning …