In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
In this work we study some probabilistic models for the random generation of words over a given alphabet used in the literature in connection with pattern statistics. Our goal is t...
Service-oriented architectures and Web service infrastructure provide the ideal framework for interconnecting organizations and for defining distributed business applications. The...
Abstract. We define Probabilistic Constrained W-grammars (PCWgrammars), a two-level formalism capable of capturing grammatical frameworks used in two state of the art parsers, nam...