A computational framework for the solution of infinite-dimensional Bayesian statistical inverse problems with application to global seismic inversion

A computational framework for the solution of infinite-dimensional Bayesian statistical inverse problems with application to global seismic inversion

Quantifying uncertainties in large-scale forward and inverse PDE simulations has emerged as a central challenge facing the field of computational science and engineering. The promise of modeling and simulation for prediction, design, and control cannot be fully realized unless uncertainties in model...

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Bibliographic Details
Main Author: Martin, James Robert, Ph. D.
Other Authors: Ghattas, Omar N.
Format: Others
Language:en
Published: 2015
Subjects:
Bayesian inference
Infinite-dimensional inverse problems
Uncertainty quantification
Low-rank approximation
Optimality
Scalable algorithms
High performance computing
Markov chain Monte Carlo
Stochastic Newton
Seismic wave propagation
Online Access:http://hdl.handle.net/2152/31374

Internet

http://hdl.handle.net/2152/31374

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