Computational Inverse Problems Governed by PDEs
Alen Alexanderian(Author)
Society for Industrial & Applied Mathematics,U.S. (Publisher)
Published on 13. March 2026
Book
Paperback/Softback
320 pages
978-1-61197-881-0 (ISBN)
Description
This textbook focuses on computational methods for inverse problems that are governed by partial differential equations (PDEs). The author considers deterministic and Bayesian formulations and highlights how traditional tools from deterministic inversion can be integrated into solution methods for Bayesian inverse problems. Advanced topics such as post-optimality sensitivity analysis, optimal design of experiments, and Bayesian inversion under model uncertainty are also included.
Computational Inverse Problems Governed by PDEs offers readers a balance of theoretical and computational insight, an example-driven approach that provides an accessible presentation, and over 150 theoretical and computational exercises.
Computational Inverse Problems Governed by PDEs offers readers a balance of theoretical and computational insight, an example-driven approach that provides an accessible presentation, and over 150 theoretical and computational exercises.
More details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
ISBN-13
978-1-61197-881-0 (9781611978810)
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Schweitzer Classification
Person
Alen Alexanderian is an associate professor of mathematics at North Carolina State University. His work focuses on computational methods for inverse problems governed by PDEs, optimal design of experiments for infinite-dimensional Bayesian inverse problems, and uncertainty quantification. His research is driven by applications in porous media flow and advection diffusion reaction processes modeling heat and mass transport, as well as applications in the life sciences.