We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for...
Despina Kontos, Vasileios Megalooikonomou, Marc J....
In simulation modeling and analysis, there are two situations where there is uncertainty about the number of parameters needed to specify a model. The first is in input modeling w...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...
Abstract. Many efforts have been involved in association study of quantitative phenotypes and expressed genes. The key issue is how to efficiently identify phenotype-associated gen...