270 search results - page 32 / 54 » Hierarchical Gaussian process latent variable models |
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UAI
2003
15 years 1 months ago
2003
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
DATE
2008
IEEE
15 years 6 months ago
2008
IEEE
Shrinking feature sizes and process variations are of increasing concern in modern technology. It is urgent that we develop statistical interconnect timing models which are harmon...
MICCAI
2004
Springer
16 years 18 days ago
2004
Springer
3D Bayesian regularization applied to diffusion tensor MRI is presented here. The approach uses Markov Random Field ideas and is based upon the definition of a 3D neighborhood syst...
ICASSP
2011
IEEE
14 years 3 months ago
2011
IEEE
A dependent hierarchical beta process (dHBP) is developed as a prior for data that may be represented in terms of a sparse set of latent features (dictionary elements), with covar...
ICA
2007
Springer
15 years 5 months ago
2007
Springer
We extend the Gaussian scale mixture model of dependent subspace source densities to include non-radially symmetric densities using Generalized Gaussian random variables linked by ...