Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
Speech has a property that the speech unit preceding a speech pause tends to lengthen. This work presents the use of a dynamic Bayesian network to model the prepausal lengthening ...
Ning Ma, Chris Bartels, Jeff A. Bilmes, Phil Green
In this paper we present a new model for the requirements analysis of a system. We offer a conceptual model defined following a visual modeling language, called dependence networks...
Guido Boella, Leendert van der Torre, Serena Villa...
Abstract. In a biological cell, cellular functions and the genetic regulatory apparatus are implemented and controlled by a network of chemical reactions in which regulatory protei...
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...