Efficiently sampling functions from Gaussian process posteriors.
James T. WilsonViacheslav BorovitskiyAlexander TereninPeter MostowskyMarc Peter DeisenrothPublished in: ICML (2020)
Keyphrases
- gaussian process
- gaussian processes
- hyperparameters
- gaussian process regression
- bayesian framework
- regression model
- approximate inference
- random sampling
- semi supervised
- gaussian process classification
- bayesian inference
- model selection
- latent variables
- posterior distribution
- expectation propagation
- sparse approximations
- sample size
- marginal likelihood
- covariance function
- gaussian process models
- cross validation
- worst case
- sparse approximation
- machine learning