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» Variational Bayesian image modelling
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DSP
2007
14 years 11 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
92
Voted
BIBE
2008
IEEE
137views Bioinformatics» more  BIBE 2008»
15 years 6 months ago
A sparse variational Bayesian approach for fMRI data analysis
— The aim of this work is to propose a new approach for the determination of the design matrix in fMRI experiments. The design matrix embodies all available knowledge about exper...
Vangelis P. Oikonomou, Evanthia E. Tripoliti, Dimi...
CVIU
2007
193views more  CVIU 2007»
14 years 11 months ago
Interpretation of complex scenes using dynamic tree-structure Bayesian networks
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
Sinisa Todorovic, Michael C. Nechyba
101
Voted
CVPR
1999
IEEE
16 years 1 months ago
Explaining Optical Flow Events with Parameterized Spatio-Temporal Models
A spatio-temporal representation for complex optical flow events is developed that generalizes traditional parameterized motion models (e.g. affine). These generative spatio-tempo...
Michael J. Black
ICONIP
2007
15 years 1 months ago
Natural Conjugate Gradient in Variational Inference
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...