270 search results - page 18 / 54 » Hierarchical Gaussian process latent variable models |
89
Voted
ICA
2007
Springer
15 years 3 months ago
2007
Springer
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
103
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NIPS
2007
15 years 1 months ago
2007
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
CVPR
2005
IEEE
16 years 1 months ago
2005
IEEE
We address the issue of modelling facial expressions for realistic 3D avatar animation. We introduce a hierarchical decomposition of a human face into different components and mod...
ICDM
2007
IEEE
15 years 6 months ago
2007
IEEE
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...
100
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ICASSP
2010
IEEE
14 years 12 months ago
2010
IEEE
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...