Localization for MCMC: sampling high-dimensional posterior distributions with local structure

Localization for MCMC: sampling high-dimensional posterior distributions with local structure

We investigate how ideas from covariance localization in numerical weather prediction can be used in Markov chain Monte Carlo (MCMC) sampling of high-dimensional posterior distributions arising in Bayesian inverse problems. To localize an inverse problem is to enforce an anticipated “local” structur...

Full description

Bibliographic Details
Main Authors: Morzfeld, M., Tong, X.T., Marzouk, Youssef M
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Format: Article
Language:English
Published: Elsevier BV 2019
Online Access:https://hdl.handle.net/1721.1/122929

Internet

https://hdl.handle.net/1721.1/122929

Similar Items