Large-Scale Inverse Problems and Quantification of Uncertainty Book Reviews

AUTHOR
Lorenz Biegler, George Biros, Omar Ghattas, Matthias Heinkenschloss, David Keyes, Bani Mallick, Luis Tenorio, Bart van Bloemen Waanders, Karen Willcox & Youssef Marzouk
SCORE
0
TOTAL RATINGS
132

Large-Scale Inverse Problems and Quantification of Uncertainty by Lorenz Biegler, George Biros, Omar Ghattas, Matthias Heinkenschloss, David Keyes, Bani Mallick, Luis Tenorio, Bart van Bloemen Waanders, Karen Willcox & Youssef Marzouk Book Summary

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.

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Book Name Large-Scale Inverse Problems and Quantification of Uncertainty
Genre Mathematics
Published
Language English
E-Book Size 24.02 MB

Large-Scale Inverse Problems and Quantification of Uncertainty (Lorenz Biegler, George Biros, Omar Ghattas, Matthias Heinkenschloss, David Keyes, Bani Mallick, Luis Tenorio, Bart van Bloemen Waanders, Karen Willcox & Youssef Marzouk) Book Reviews 2024

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Lorenz Biegler, George Biros, Omar Ghattas, Matthias Heinkenschloss, David Keyes, Bani Mallick, Luis Tenorio, Bart van Bloemen Waanders, Karen Willcox & Youssef Marzouk - Large-Scale Inverse Problems and Quantification of Uncertainty Discussions & Comments

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Other Books from Lorenz Biegler, George Biros, Omar Ghattas, Matthias Heinkenschloss, David Keyes, Bani Mallick, Luis Tenorio, Bart van Bloemen Waanders, Karen Willcox & Youssef Marzouk
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Summary of Large-Scale Inverse Problems and Quantification of Uncertainty by Lorenz Biegler, George Biros, Omar Ghattas, Matthias Heinkenschloss, David Keyes, Bani Mallick, Luis Tenorio, Bart van Bloemen Waanders, Karen Willcox & Youssef Marzouk

The Large-Scale Inverse Problems and Quantification of Uncertainty book written by Lorenz Biegler, George Biros, Omar Ghattas, Matthias Heinkenschloss, David Keyes, Bani Mallick, Luis Tenorio, Bart van Bloemen Waanders, Karen Willcox & Youssef Marzouk was published on 24 June 2011, Friday in the Mathematics category. A total of 132 readers of the book gave the book 0 points out of 5.

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