Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancer cell's molecular state and ...
Matthew Holford, James P. McCusker, Kei-Hoi Cheung...
We introduce a new notion of bisimulation, called event bisimulation on labelled Markov processes (LMPs) and compare it with the, now standard, notion of probabilistic bisimulatio...
Abstract. The upper-level ontologies are theories that capture the most common concepts, which are relevant for many of the tasks involving knowledge extraction, representation, an...
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...