Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixedpo...
In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reason...
This paper describes a new technique for free-form object segmentation from a single arbitrary-viewed range image. The aim is to derive a surface description of objects that may va...
We extend the differential approach to inference in Bayesian networks (BNs) (Darwiche, 2000) to handle specific problems that arise in the context of dynamic Bayesian networks (D...
This paper introduces a new framework for error concealment in block-based image coding systems: sequential recovery. Unlike previous approaches that simultaneously recover the pix...