NIPS
1998
15 years 8 days ago
1998
We study probabilistic inference in large, layered Bayesian networks represented as directed acyclic graphs. We show that the intractability of exact inference in such networks do...
83
Voted
NIPS
2008
15 years 11 days ago
2008
A series of corrections is developed for the fixed points of Expectation Propagation (EP), which is one of the most popular methods for approximate probabilistic inference. These ...
100
Voted
ICML
2004
IEEE
15 years 11 months ago
2004
IEEE
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
101
Voted
ECCV
2008
Springer
16 years 25 days ago
2008
Springer
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...