4 papers · 1 filter
Statistical inverse learning and -regularization
Abhishake Rastogi, Tatiana A. Bubba, Tapio Helin +1
We study the recovery of sparse functions from finite, noisy, and indirect observations in the framework of statistical inverse learning. The unknown is modeled as an element of $\…
Learning sparsity-promoting regularizers for linear inverse problems
Giovanni S. Alberti, Ernesto De Vito, Tapio Helin +3
This paper introduces a novel approach to learning sparsity-promoting regularizers for solving linear inverse problems. We develop a bilevel optimization framework to select an opt…
Learning a Gaussian Mixture for Sparsity Regularization in Inverse Problems
Giovanni S. Alberti, Luca Ratti, Matteo Santacesaria +1
In inverse problems, it is widely recognized that the incorporation of a sparsity prior yields a regularization effect on the solution. This approach is grounded on the a priori as…
Learned reconstruction methods for inverse problems: sample error estimates
Luca Ratti
Learning-based and data-driven techniques have recently become a subject of primary interest in the field of reconstruction and regularization of inverse problems. Besides the deve…