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