Approximate Inference in Collective Graphical Models.
Daniel SheldonTao SunAkshat KumarThomas G. DietterichPublished in: ICML (3) (2013)
Keyphrases
- approximate inference
- graphical models
- belief propagation
- probabilistic inference
- exact inference
- random variables
- probabilistic model
- variational methods
- probabilistic graphical models
- markov networks
- bayesian networks
- factor graphs
- loopy belief propagation
- conditional random fields
- dynamic bayesian networks
- structure learning
- belief networks
- parameter learning
- conditional independence
- markov chain monte carlo
- message passing
- free energy
- markov random field
- partition function
- undirected graphical models
- structured prediction
- exponential family