Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems

Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems

We considered a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a high dimension spatial field. The Bayesian approach contains a natural mechanism for regularization in the form of prior information, can incorporate information from heterogeneous sources and provides...

Full description

Bibliographic Details
Main Author: Mondal, Anirban
Other Authors: Mallick, Bani K.
Format: Others
Language:en_US
Published: 2012
Subjects:
Bayesian Hierarchical Model
Karhunen Loeve Expansion
Two Stage Reversible Jump Markov Chain Monte Carlo
Discrete Cosine Transform
Emulator
Bayesian Multivariate Adaptive Regression Splines
Online Access:http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905

Internet

http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905

Similar Items