Applied Mathematics in Inverse Problems and Uncertainty Quantification
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".
Deadline for manuscript submissions: 31 July 2024 | Viewed by 584
Special Issue Editors
Interests: deep learning; generative models; variational inference; inverse problems; uncertainty quantification; signal processing
Interests: inverse problems; applied mathematics; scientific computing
Special Issue Information
Dear Colleagues,
Inverse problems are ubiquitous in many areas of science and engineering where the goal is to reliably determine the hidden properties of a system or process from observations of its output. Inverse problems are often ill-posed, meaning that small changes in the data can lead to significant variations in the solution. Additionally, due to non-trivial nullspace of the forward operator and measurement noise, solutions to inverse problems commonly arising in real-world applications cannot be uniquely determined. Uncertainty quantification plays a critical role in such problems by providing measures of the reliability and robustness of the inferred solutions.
This Special Issue aims to present recent advances in the mathematical theory, numerical methods, applications of inverse problems and uncertainty quantification. The focus is on the development of innovative mathematical and computational tools for solving complex problems, as well as their practical applications in fields such as medical imaging, geophysics, finance, and materials science. The articles in this Special Issue cover a wide range of topics, including Bayesian inference, optimization techniques, regularization methods, high-dimensional data analysis, and machine learning.
We cordially invite authors to submit their original research articles that align with the scope of this Special Issue.
Dr. Ali Siahkoohi
Dr. Bamdad Hosseini
Dr. Gabrio Rizzuti
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- inverse problems
- uncertainty quantification
- Bayesian inference
- optimization
- regularization
- machine learning
