Discrete EVent Systems Specification (DEVS) formalism supports specification of discrete event models in a hierarchical modular manner. This paper proposes a DEVS modeling languag...
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...
We present a fully probabilistic stick-figure model that uses a nonparametric Bayesian distribution over trees for its structure prior. Sticks are represented by nodes in a tree i...
Edward Meeds, David A. Ross, Richard S. Zemel, Sam...
Abstract. A hierarchical model based on the Multivariate Autoregessive (MAR) process is proposed to jointly model neurological time-series collected from multiple subjects, and to ...
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...