A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables
Kevin P. MurphyPublished in: CoRR (2013)
Keyphrases
- variational approximation
- latent variables
- bayesian networks
- exact inference
- probabilistic model
- hidden variables
- random variables
- approximate inference
- variational bayes
- graphical models
- posterior distribution
- prior knowledge
- topic models
- probabilistic graphical models
- gaussian process
- probability distribution
- structured prediction
- structure learning
- conditional probabilities
- bayesian inference
- variational inference
- factor graphs
- conditional independence
- probabilistic inference
- generative model
- parameter learning
- bayesian learning
- dynamic bayesian networks
- belief networks
- variational methods
- regression model
- parameter estimation
- belief propagation
- probabilistic latent semantic analysis
- message passing
- co occurrence
- learning algorithm