This work takes place in the context of hierarchical stochastic models for the resolution of discrete inverse problems from low level vision. Some of these models lie on the nodes...
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 ...
Jason A. Palmer, Kenneth Kreutz-Delgado, Bhaskar D...
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
– The paper deals with fitting of planar patches to 3D laser range data obtained by a mobile robot. The number and the initial position of the patches are unknown, hence their es...
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...