Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...