Efficiently sampling functions from Gaussian process posteriors.
James T. WilsonViacheslav BorovitskiyAlexander TereninPeter MostowskyMarc Peter DeisenrothPublished in: CoRR (2020)
Keyphrases
- gaussian process
- gaussian processes
- hyperparameters
- regression model
- gaussian process regression
- bayesian framework
- approximate inference
- random sampling
- gaussian process classification
- latent variables
- model selection
- semi supervised
- posterior distribution
- gaussian process models
- bayesian inference
- sample size
- expectation propagation
- marginal likelihood
- covariance function
- posterior probability
- prior information
- sparse approximation
- markov chain monte carlo
- sparse approximations