We present a new approach to inferring a probability distribution which is incompletely specified by a number of linear constraints. We argue that the currently most popular appro...
Subtyping rules can be fairly complex for union types, due to interactions with other types, such as function types. Furthermore, these interactions turn out to depend on the calc...
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...