Previous work on context-specific independence in Bayesian networks is driven by a common goal, namely to represent the conditional probability tables in a most compact way. In th...
Abstract. Programmers employing inference in Bayesian networks typically rely on the inclusion of the model as well as an inference engine into their application. Sophisticated inf...
Abstract. Dynamic Bayesian networks (DBNs) extend Bayesian networks from static domains to dynamic domains. The only known generic method for exact inference in DBNs is based on dy...
Abstract. We address the problem of extracting Minimal Unsatisfiable Cores (MUCs) from constraint networks. This computationally hard problem has a practical interest in many appli...
Fred Hemery, Christophe Lecoutre, Lakhdar Sais, Fr...
Abstract. It is known from psychology and neuroscience that multimodal integration of sensory information enhances the perception of stimuli that are corrupted in one or more modal...