An extension of the differential approach for Bayesian network inference to dynamic Bayesian networks.
Boris BrandhermAnthony JamesonPublished in: Int. J. Intell. Syst. (2004)
Keyphrases
- dynamic bayesian networks
- bayesian network inference
- approximate inference
- bayesian networks
- graphical models
- belief propagation
- probabilistic inference
- parameter estimation
- structure learning
- gaussian process
- message passing
- latent variables
- probabilistic model
- particle filtering
- random variables
- conditional random fields
- conditional probabilities
- least squares
- conditional independence
- posterior probability
- support vector
- feature selection
- markov networks
- stereo matching
- graph cuts
- markov random field