Finding the M Most Probable Configurations in Arbitrary Graphical Models.
Chen YanoverYair WeissPublished in: NIPS (2003)
Keyphrases
- gaussian process
- approximate inference
- graphical models
- belief networks
- latent variables
- probabilistic model
- random variables
- belief propagation
- probabilistic graphical models
- exact inference
- loopy belief propagation
- probabilistic inference
- factor graphs
- markov networks
- conditional random fields
- statistical inference
- conditional independence
- graph structure
- structure learning
- bayesian networks
- probability distribution
- undirected graphical models
- markov logic networks
- statistical relational learning
- message passing