Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks.
David BarberPeter SollichPublished in: NIPS (1999)
Keyphrases
- belief networks
- approximate inference
- graphical models
- probabilistic inference
- exact inference
- expectation propagation
- belief propagation
- variational methods
- probabilistic model
- conditional probabilities
- message passing
- bayesian networks
- conditional random fields
- probability distribution
- random variables
- dynamic bayesian networks
- structured prediction
- gaussian process
- maximum likelihood
- stereo matching
- generative model
- computer vision
- latent variables
- artificial neural networks
- graph cuts