We present a method for efficiently generating a representation of a multi-modal posterior probability distribution. The technique combines ideas from RANSAC and particle filterin...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Evolutionary structural testing is an approach to automatically generating test cases that achieve high structural code coverage. It typically uses genetic algorithms (GAs) to sea...
We investigate the understanding of landmarks using a model of embedding procedures that sees affordances established on three levels. On the first level there are landmark experie...
Self-organizing models develop realistic cortical structures when given approximations of the visual environment as input, and are an effective way to model the development of fac...