High-Dimensional Gaussian Process Inference with Derivatives.
Filip de RoosAlexandra GessnerPhilipp HennigPublished in: CoRR (2021)
Keyphrases
- gaussian process
- high dimensional
- covariance function
- variational inference
- gaussian processes
- expectation propagation
- bayesian framework
- regression model
- gaussian process regression
- approximate inference
- hyperparameters
- latent variables
- model selection
- latent space
- higher order
- bayesian inference
- gaussian process classification
- sparse approximations
- semi supervised
- dynamic bayesian networks
- probabilistic inference
- dimensionality reduction
- variational bayes
- high dimensional data
- low dimensional
- nearest neighbor
- bayesian networks
- gaussian process models
- parameter space
- dirichlet process
- data points
- human pose estimation
- machine learning
- image segmentation
- feature space
- text mining
- error rate
- cross validation