Computing the M Most Probable Modes of a Graphical Model.
Chao ChenVladimir KolmogorovYan ZhuDimitris N. MetaxasChristoph H. LampertPublished in: AISTATS (2013)
Keyphrases
- graphical models
- belief networks
- belief propagation
- approximate inference
- probabilistic inference
- random variables
- probabilistic graphical models
- probabilistic model
- bayesian networks
- markov networks
- structure learning
- conditional random fields
- graph structure
- map inference
- factor graphs
- gaussian graphical models
- statistical inference
- exact inference
- probability distribution
- bayesian belief networks
- graphical structure
- directed acyclic
- loopy belief propagation
- conditional independence
- model selection
- conditional dependencies
- degrees of freedom