Sampling for Approximate Inference in Continuous Time Bayesian Networks.
Yu FanChristian R. SheltonPublished in: ISAIM (2008)
Keyphrases
- approximate inference
- variational approximation
- markov chain monte carlo
- graphical models
- exact inference
- belief propagation
- probabilistic inference
- parameter estimation
- message passing
- gaussian process
- latent variables
- variational methods
- bayesian networks
- factor graphs
- dynamic bayesian networks
- probabilistic graphical models
- random sampling
- bayesian inference
- structured prediction
- em algorithm
- sample size
- conditional random fields
- variational inference
- monte carlo
- kullback leibler
- variational bayes
- generative model
- posterior distribution
- semi supervised
- probabilistic model
- machine learning