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INFSOF
2006
158views more  INFSOF 2006»
15 years 6 months ago
DEVSpecL: DEVS specification language for modeling, simulation and analysis of discrete event systems
Discrete EVent Systems Specification (DEVS) formalism supports specification of discrete event models in a hierarchical modular manner. This paper proposes a DEVS modeling languag...
Ki Jung Hong, Tag Gon Kim
CVPR
2005
IEEE
16 years 8 months ago
Mixture Trees for Modeling and Fast Conditional Sampling with Applications in Vision and Graphics
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...
Frank Dellaert, Vivek Kwatra, Sang Min Oh
CVPR
2008
IEEE
16 years 8 months ago
Learning stick-figure models using nonparametric Bayesian priors over trees
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...
IPMI
2005
Springer
16 years 7 months ago
Bayesian Population Modeling of Effective Connectivity
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 ...
Eric R. Cosman Jr., William M. Wells III
ACCV
2009
Springer
16 years 1 months ago
Levels of Details for Gaussian Mixture Models
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...
Vincent Garcia, Frank Nielsen, Richard Nock