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Computational Uncertainty Quantification for Inverse Problems

Download or Read eBook Computational Uncertainty Quantification for Inverse Problems PDF written by Johnathan M. Bardsley and published by SIAM. This book was released on 2018-08-01 with total page 141 pages. Available in PDF, EPUB and Kindle.
Computational Uncertainty Quantification for Inverse Problems
Author :
Publisher : SIAM
Total Pages : 141
Release :
ISBN-10 : 9781611975376
ISBN-13 : 1611975379
Rating : 4/5 (76 Downloads)

Book Synopsis Computational Uncertainty Quantification for Inverse Problems by : Johnathan M. Bardsley

Book excerpt: This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB? code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers. Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.


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