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CPAIOR
2008
Springer
15 years 1 months ago
Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting
We consider the problem of estimating the model count (number of solutions) of Boolean formulas, and present two techniques that compute estimates of these counts, as well as eith...
Lukas Kroc, Ashish Sabharwal, Bart Selman
UAI
2004
15 years 1 months ago
On the Choice of Regions for Generalized Belief Propagation
Generalized belief propagation (GBP) has proven to be a promising technique for approximate inference tasks in AI and machine learning. However, the choice of a good set of cluste...
Max Welling
NIPS
2003
15 years 1 months ago
Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation
The detection and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes, and the high dimensio...
Leonid Sigal, Michael Isard, Benjamin H. Sigelman,...
ICML
2010
IEEE
15 years 25 days ago
Continuous-Time Belief Propagation
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman
CORR
2008
Springer
234views Education» more  CORR 2008»
14 years 12 months ago
Bayesian Compressive Sensing via Belief Propagation
Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...
Dror Baron, Shriram Sarvotham, Richard G. Baraniuk