Posterior consistency for Gaussian process approximations of Bayesian posterior distributions.
Andrew M. StuartAretha L. TeckentrupPublished in: Math. Comput. (2018)
Keyphrases
- posterior distribution
- gaussian process
- hyperparameters
- expectation propagation
- latent variables
- bayesian framework
- closed form
- gaussian processes
- free energy
- model selection
- bayesian learning
- cross validation
- bayesian inference
- random sampling
- approximate inference
- variational bayes
- support vector
- noise level
- maximum a posteriori
- prior information
- variational inference
- em algorithm
- sample size
- fully bayesian
- markov chain monte carlo
- probabilistic model
- incremental learning
- posterior probability
- probability distribution
- bayesian methods
- generative model
- maximum likelihood
- markov chain monte carlo methods
- parameter estimation
- prior knowledge
- missing values
- variational methods
- regression model
- upper bound
- dirichlet process
- decision trees
- learning algorithm