Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
Comprehending results from 3D CFD simulation is a difficult task. In this paper, we present a semantics-based approach to featurebased volume rendering of 3D flow data. We make ...
Spatio-temporal databases have been the focus of considerable research activity over a significant period. However, there are as of yet very few prototypes of complete systems, f...
Norman W. Paton, Alvaro A. A. Fernandes, Tony Grif...
Background: SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platfor...
Katerina Michalickova, Gary D. Bader, Michel Dumon...
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...