Special issue on Computational Optimal Transport Theory for Inverse Problems
Guest Editors
- Gang Bao, Zhejiang University, China
- Bjorn Engquist, University of Texas at Austin, USA
- Kui Ren, Columbia University, USA
- Yunan Yang, Cornell University, USA
Typical eigenvectors of the Hessian matrices for data mismatch functionals based on the classical least-squares (left) and the 2-Wasserstein metric (right) in full waveform inversion (FWI).
Scope
In recent years, great efforts have been devoted to developing new computational methods for the numerical solutions of imaging and inverse problems. Concepts and technical tools from optimal transport theory have been studied extensively in the context of inverse problems and imaging and have been successfully applied to solve different types of inverse problems, including but not limited to, computed tomography, seismic imaging with the wave equation, inverse coefficients for elliptic PDEs from boundary data, hybrid inverse problems with internal data, data assimilation, and inversion of dynamical systems. Extensive computational evidence is available to demonstrate the advantages of such new techniques, and theoretical understandings of their performance are gradually being developed.
The rationale for this special issue is to highlight, in a systematic way, the recent development in computational imaging and inversion techniques based on optimal transport theory. Through this, we wish to facilitate new discussions and collaborations between researchers working on different aspects of optimal transport theory for inverse problems to further strengthen the theoretical and computational developments of the algorithms. This is also an opportunity to provide (especially junior) researchers outside of the research area with a coherent picture of this fascinating research field.
Submission process
We encourage submissions from all authors whose work fits with the scope of this focus collection. The collection will also feature invited contributions. All focus issue articles are subject to the same review process as regular articles. Authors are invited to contact one of the guest editors, or the IP journal team directly, to discuss the suitability of their work prior to submission.
Please submit your article via our online submission form.You should submit the appropriate article type for your submission then choose 'Special issue on Computational Optimal Transport Theory for Inverse Problems' from the drop-down menu.
Deadline for submissions
The target deadline for submissions is 31 October 2024 though we can be flexible where necessary. We encourage early submission where possible, as articles will be published on acceptance without being delayed by other papers in the collection.