Bayesian networks (BN) constitute a useful tool to model the joint distribution of a set of random variables of interest. To deal with the problem of learning sensible BN models fr...
This paper presents a novel algorithm for document clustering based on a combinatorial framework of the Principal Direction Divisive Partitioning (PDDP) algorithm [1] and a simpli...
Tracking of tubular elongated structures is an important goal in a wide range of biomedical imaging applications. A Bayesian tube tracking algorithm is presented that allows to eas...
Michiel Schaap, Ihor Smal, Coert Metz, Theo van Wa...
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...