Large-Scale Inverse Problems and Quantification of Uncertainty (Wiley Series in Computational Statistics #708)

Synopsis

This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale inverse problems critically depends on methods to reduce computational cost. Recent research approaches tackle this challenge in a variety of different ways. Many of the computational frameworks highlighted in this book build upon state-of-the-art methods for simulation of the forward problem, such as, fast Partial Differential Equation (PDE) solvers, reduced-order models and emulators of the forward problem, stochastic spectral approximations, and ensemble-based approximations, as well as exploiting the machinery for large-scale deterministic optimization through adjoint and other sensitivity analysis methods. Key Features: Brings together the perspectives of researchers in areas of inverse problems and data assimilation. Assesses the current state-of-the-art and identify needs and opportunities for future research. Focuses on the computational methods used to analyze and simulate inverse problems. Written by leading experts of inverse problems and uncertainty quantification. Graduate students and researchers working in statistics, mathematics and engineering will benefit from this book.

Copyright:

2010

Book Details

Book Quality:

Publisher Quality

Book Size:

392 Pages

ISBN-13:

9780470685860

Related ISBNs:

9780470685853, 9780470697436

Publisher:

Wiley

Date of Addition:

12/21/19

Copyrighted By:

N/A

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Mathematics and Statistics

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.

Edited by:

Lorenz Biegler

Edited by:

George Biros

Edited by:

Omar Ghattas

Edited by:

Matthias Heinkenschloss

Edited by:

David Keyes

Edited by:

Bani Mallick

Edited by:

Luis Tenorio

Edited by:

Bart van Bloemen Waanders

Edited by:

Karen Willcox

Edited by:

Youssef Marzouk