Approximate Inference and Forecast Algorithms in Graphical Models for Partially Observed Dynamic Systems.
Alberto LekuonaBeatriz LacruzPilar LasalaPublished in: AISTATS (1997)
Keyphrases
- graphical models
- approximate inference
- dynamic systems
- belief propagation
- loopy belief propagation
- variational methods
- exact inference
- probabilistic inference
- probabilistic graphical models
- factor graphs
- partially observed
- parameter estimation
- random variables
- conditional random fields
- undirected graphical models
- bayesian networks
- complex systems
- generalized belief propagation
- markov chain monte carlo
- message passing
- probabilistic model
- belief networks
- gaussian process
- markov random field
- dynamic bayesian networks
- structure learning
- markov networks
- latent variables
- dynamical systems
- upper and lower bounds
- exponential family
- partition function