An intervention on a variable removes the influences that usually have a causal effect on that variable. Gates [1] are a general-purpose graphical modelling notation for representing such context-specific independencies in the structure of a graphical model. We extend d-separation to cover gated graphical models and show that it subsumes do calculus [2] when gates are used to represent interven...

We apply a Bayesian belief network (BN) approach to vowel duration modelling, whereby vowel segment duration is modelled as a hybrid Bayesian network consisting of discrete and continuous nodes, with the nodes in the network representing linguistic factors that affect segment duration. Factor interaction is modelled in a concise way by causal relationships among the nodes in a directed acyclic ...

Evaporation phenomena is a effective climate component on water resources management and has special importance in agriculture. In this paper, Bayesian belief networks (BBNs) as a non-linear modeling technique provide an evaporation estimation  method under uncertainty. As a case study, we estimated the surface water evaporation of the Persian Gulf and worked with a dataset of observations ...

This paper incorporates Belief Propagation into an instance of Estimation of Distribution Algorithms called Estimation of Bayesian Networks Algorithm. Estimation of Bayesian Networks Algorithm learns a Bayesian network at each step. The objective of the proposed variation is to increase the search capabilities by extracting information of the, computationally costly to learn, Bayesian network. ...