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...
Abstract This paper presents a type-based analysis for inferring sizeand cost-equations for recursive, higher-order and polymorphic functional programs without requiring user annot...
We have been working on a unit system for end-user spreadsheets that is based on the concrete notion of units of the abstract concept of types. In previous work, we defined such ...
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...
Selection bias, caused by preferential exclusion of samples from the data, is a major obstacle to valid causal and statistical inferences; it cannot be removed by randomized exper...