Stochastic variational inference for scalable non-stationary Gaussian process regression.
Ionut PaunDirk HusmeierColin J. TorneyPublished in: Stat. Comput. (2023)
Keyphrases
- non stationary
- gaussian process regression
- variational inference
- gaussian process
- gaussian processes
- regression model
- bayesian framework
- model selection
- bayesian inference
- hyperparameters
- approximate inference
- probabilistic model
- mixture model
- latent variables
- posterior distribution
- semi supervised
- generative model
- topic models
- latent dirichlet allocation
- variational methods
- machine learning
- dimensionality reduction
- support vector