Previous studies have demonstrated that encoding a Bayesian network into a SAT formula and then performing weighted model counting using a backtracking search algorithm can be an ...
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
— The assessment of highly-risky situations at road intersections have been recently revealed as an important research topic within the context of the automotive industry. In thi...