Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model selection a...
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 ...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
This paper provides a study of the theoretical properties of Most Relevant Explanation (MRE) [12]. The study shows that MRE defines an implicit soft relevance measure that enables ...