Efficient Sampling of Gaussian Processes under Linear Inequality Constraints

Efficient Sampling of Gaussian Processes under Linear Inequality Constraints

In this thesis, newer Markov Chain Monte Carlo (MCMC) algorithms are implemented and compared in terms of their efficiency in the context of sampling from Gaussian processes under linear inequality constraints. Extending the framework of Gaussian process that uses Gibbs sampler, two MCMC algorithms,...

Full description

Bibliographic Details
Main Author: Brahmantio, Bayu Beta
Format: Others
Language:English
Published: Linköpings universitet, Statistik och maskininlärning 2021
Subjects:
Gaussian process
truncated multivariate Gaussian
Hamiltonian Monte Carlo
Elliptical Slice Sampling
Probability Theory and Statistics
Sannolikhetsteori och statistik
Computer Sciences
Datavetenskap (datalogi)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176246

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176246

Similar Items