When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Model-checking has turned out to be an efficient and relatively easy-to-use technique in the verification of formally described programs. However, there is one major drawback in u...
Abstract. Interoperability is a key and challenging requirement in today’s and future systems, which are often characterized by an extreme level of heterogeneity. To build an int...
Background: Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functiona...
Steffen Klamt, Julio Saez-Rodriguez, Jonathan A. L...