Subspace segmentation is the task of segmenting data
lying on multiple linear subspaces. Its applications in
computer vision include motion segmentation in video,
structure-from...
We apply a scalable approach for practical, comprehensive design space evaluation and optimization. This approach combines design space sampling and statistical inference to ident...
Background: The study of protein-small molecule interactions is vital for understanding protein function and for practical applications in drug discovery. To benefit from the rapi...
Ratna R. Thangudu, Manoj Tyagi, Benjamin A. Shoema...
Background: Genome context methods have been introduced in the last decade as automatic methods to predict functional relatedness between genes in a target genome using the patter...
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...