Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...
The paper abstracts the contents of a PhD dissertation entitled A Generic, Collaborative Framework for Interval Constraint Solving which has been recently defended. This thesis pre...
To simplify the task of obtaining information from the vast number of information sources that are available on the World Wide Web (WWW), we are building tools to build informatio...
A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a `show-and-tell' procedu...
In this paper we present a technique for automatically generating constraints on parameter derivatives that reduce ambiguity in the behaviour prediction. Starting with a behaviour...