High-Dimensional Gaussian Process Inference with Derivatives.
Filip de RoosAlexandra GessnerPhilipp HennigPublished in: ICML (2021)
Keyphrases
- gaussian process
- high dimensional
- expectation propagation
- variational inference
- covariance function
- gaussian processes
- approximate inference
- hyperparameters
- gaussian process regression
- regression model
- gaussian process classification
- bayesian framework
- bayesian inference
- model selection
- latent variables
- variational bayes
- latent space
- low dimensional
- dimensionality reduction
- higher order
- nearest neighbor
- semi supervised
- gaussian process models
- cross validation
- parameter space
- data points
- dynamic bayesian networks
- feature space
- markov chain monte carlo
- probability distribution
- dirichlet process
- high dimensional data
- bayesian networks
- density estimation
- pairwise
- data sets