Learning General Latent-Variable Graphical Models with Predictive Belief Propagation.
Borui WangGeoffrey GordonPublished in: AAAI (2020)
Keyphrases
- graphical models
- belief propagation
- approximate inference
- latent variables
- probabilistic model
- random variables
- message passing
- probabilistic graphical models
- factor graphs
- structured prediction
- markov networks
- markov random field
- probabilistic inference
- conditional random fields
- graph cuts
- latent variable models
- hidden variables
- learning algorithm
- fixed point
- stereo matching
- loopy belief propagation
- structure learning
- exact inference
- partition function
- bayesian networks
- active learning
- conditional independence
- energy minimization
- dynamic bayesian networks
- gaussian process
- belief networks
- learning problems
- free energy
- upper bound
- pairwise