Approximate Sampling using an Accelerated Metropolis-Hastings based on Bayesian Optimization and Gaussian Processes.
Asif J. ChowdhuryGabriel TerejanuPublished in: CoRR (2019)
Keyphrases
- gaussian processes
- metropolis hastings
- posterior distribution
- hyperparameters
- gaussian process
- sampling algorithm
- model selection
- random sampling
- markov chain monte carlo
- bayesian framework
- cross validation
- bayesian methods
- closed form
- particle filtering
- latent variables
- em algorithm
- support vector
- bayesian learning
- variational bayes
- probability distribution
- bayesian inference
- variational inference
- sample size
- parameter settings
- multi task
- prior information
- maximum a posteriori
- incremental learning
- parameter estimation
- markov chain
- maximum likelihood
- probabilistic model