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NN
2002
Springer
136views Neural Networks» more  NN 2002»
13 years 7 months ago
Bayesian model search for mixture models based on optimizing variational bounds
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Naonori Ueda, Zoubin Ghahramani
BMCBI
2006
98views more  BMCBI 2006»
13 years 7 months ago
In search of functional association from time-series microarray data based on the change trend and level of gene expression
Background: The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional l...
Feng He, An-Ping Zeng
JMLR
2010
136views more  JMLR 2010»
13 years 2 months ago
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential family using the variational Bayesian expectation maximisation (VB EM) algorith...
Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti...
MOC
2011
13 years 2 months ago
Convergence of a mixed method for a semi-stationary compressible Stokes system
We propose and analyze a finite element method for a semi– stationary Stokes system modeling compressible fluid flow subject to a Navier– slip boundary condition. The veloci...
Kenneth H. Karlsen, Trygve K. Karper
VISUALIZATION
2005
IEEE
14 years 1 months ago
Rendering Tetrahedral Meshes with Higher-Order Attenuation Functions for Digital Radiograph Reconstruction
This paper presents a novel method for computing simulated x-ray images, or DRRs (digitally reconstructed radiographs), of tetrahedral meshes with higher-order attenuation functio...
Ofri Sadowsky, Jonathan D. Cohen, Russell H. Taylo...