In this paper we consider the problem of inference on a class of sets describing a collection of admissible models as … especially appealing in the target applications. Moreover, the resulting inference procedures are also more powerful than the …

corresponding factor graph representation exist.In order to perform inference in such graphs, we describe the `derivative … inference and estimation of CDNs. …

This report introduces a novel approach to performing inference and learning in Dynamic Bayesian Networks (DBN). The … traditional approach to inference and learning in DBNs involves conditioning on one or more finite-length observation sequences … solving inference problems (i.e., computing P(X|Φ)) and learning problems (i.e., computing P(Θ|Φ)) using techniques from the …