Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models.
Craig KellySomdeb SarkhelDeepak VenugopalPublished in: AISTATS (2019)
Keyphrases
- probabilistic graphical models
- gibbs sampling
- approximate inference
- exact inference
- graphical models
- belief propagation
- probabilistic inference
- parameter estimation
- bayesian networks
- latent variables
- belief networks
- topic models
- markov networks
- variational methods
- conditional random fields
- parameter learning
- dynamic bayesian networks
- structured prediction
- em algorithm
- expectation maximization
- random variables
- probabilistic model
- message passing
- markov chain monte carlo
- gaussian process
- markov chain
- machine learning
- first order logic
- information retrieval
- least squares
- latent dirichlet allocation
- artificial neural networks