Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC.
Roger FrigolaFredrik LindstenThomas B. SchönCarl E. RasmussenPublished in: NIPS (2013)
Keyphrases
- bayesian inference
- gaussian process
- hyperparameters
- variational inference
- expectation propagation
- probabilistic model
- hidden variables
- gaussian processes
- bayesian framework
- bayesian methods
- markov chain monte carlo
- model selection
- state space
- generative model
- approximate inference
- posterior distribution
- variational bayes
- particle filter
- learning process
- latent variables
- gaussian process models
- prior knowledge
- learning algorithm
- covariance function
- dynamic bayesian networks
- bayesian model
- prior information
- reinforcement learning
- gaussian process regression
- incremental learning
- monte carlo
- cross validation
- markov chain
- graphical models
- active learning
- bayesian networks