Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights.
Theofanis KaraletsosThang D. BuiPublished in: CoRR (2020)
Keyphrases
- gaussian process
- gaussian processes
- bayesian framework
- neural network
- hyperparameters
- posterior distribution
- marginal likelihood
- prior distribution
- posterior probability
- fully bayesian
- variational inference
- bayesian nonparametric
- approximate inference
- dirichlet process
- gaussian process regression
- dynamical models
- regression model
- latent variables
- bayesian inference
- gaussian process classification
- back propagation
- expectation propagation
- model selection
- maximum a posteriori
- bayesian methods
- semi supervised
- dynamical model
- prior knowledge
- sparse approximations
- prior information
- artificial neural networks
- covariance function
- maximum likelihood
- linear combination
- generative model
- bayesian networks
- gaussian process models
- support vector
- incremental learning
- closed form
- expectation maximization
- graphical models
- machine learning