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