We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
Advances in wireless communications, positioning technology, and other hardware technologies combine to enable a range of applications that use a mobile user's geo-spatial da...
Laurynas Speicys, Christian S. Jensen, Augustas Kl...
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to bett...
Paola M. V. Rancoita, Marcus Hutter, Francesco Ber...