In recent years, there has been a cross-fertilization of ideas between computational neuroscience models of the operation of the neocortex and artificial intelligence models of mac...
John Thornton, Jolon Faichney, Michael Blumenstein...
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Background: Identification of approximate tandem repeats is an important task of broad significance and still remains a challenging problem of computational genomics. Often there ...
Vladimir Paar, Nenad Pavin, Ivan Basar, Marija Ros...
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
The hierarchical generalized Voronoi graph (HGVG) is a new roadmap developed for sensor-based exploration in unknown environments. This paper defines the HGVG structure: a robot c...