Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions.
Toni KarvonenGeorge WynneFilip TronarpChris J. OatesSimo SärkkäPublished in: SIAM/ASA J. Uncertain. Quantification (2020)
Keyphrases
- gaussian process
- maximum likelihood estimation
- mixture of gaussians
- expectation propagation
- marginal likelihood
- gaussian processes
- covariance function
- sparse approximations
- hyperparameters
- maximum likelihood
- em algorithm
- gaussian process regression
- approximate inference
- latent variables
- bayesian framework
- regression model
- model selection
- parameter estimation
- expectation maximization
- probability distribution
- semi supervised
- closed form
- cross validation
- sparse representation
- computer vision
- density function
- data mining
- least squares
- feature space
- support vector