Sparsity Promoting Optimal Transport regularization for superresolution and data-driven models
Organization:
Funded by: | UT/EWI |
PhD: |  |
Supervisor: Daily supervisor: |   |
Collaboration: | - |
Description:
In this project, we plan to study the properties of solutions of sparsity-promoting models. In particular, we will focus on static and dynamic models regularized with Optimal Transport energies, with the goal of understanding the superresolution properties of Inverse Problems in the presence of noise. We will then apply the developed theory to analyze the dynamics and improve the training of Machine Learning models.
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