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» A Hierarchical Latent Variable Model for Data Visualization
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BMCBI
2007
138views more  BMCBI 2007»
13 years 5 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
CSDA
2011
13 years 9 days ago
Hierarchical multilinear models for multiway data
Reduced-rank decompositions provide descriptions of the variation among the elements of a matrix or array. In such decompositions, the elements of an array are expressed as produc...
Peter D. Hoff
ARCS
2004
Springer
13 years 10 months ago
Heterogenous Data Fusion via a Probabilistic Latent-Variable Model
In a pervasive computing environment, one is facing the problem of handling heterogeneous data from different sources, transmitted over heterogeneous channels and presented on het...
Kai Yu, Volker Tresp
ESANN
2006
13 years 6 months ago
A Gaussian process latent variable model formulation of canonical correlation analysis
Abstract. We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1...
Gayle Leen, Colin Fyfe
CORR
2010
Springer
168views Education» more  CORR 2010»
13 years 3 months ago
Gaussian Process Structural Equation Models with Latent Variables
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by...
Ricardo Silva