405 search results - page 10 / 81 » Bayesian Gaussian Process Latent Variable Model |
UAI
2004
14 years 10 months ago
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
104
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CVPR
2009
IEEE
2009
IEEE
Switching Gaussian Process Dynamic Models for simultaneous composite motion tracking and recognition
15 years 1 months ago
Traditional dynamical systems used for motion tracking cannot effectively handle high dimensionality of the motion states and composite dynamics. In this paper, to address both is...
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
ICCV
2005
IEEE
15 years 3 months ago
2005
IEEE
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...