47 citations · 47 across the 6 of their papers we have counts for
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Spectral Function Space Learning and Numerical Linear Algebra Networks for Solving Linear Inverse Problems
Andrea Aspri, Leon Frischauf, Otmar Scherzer
We consider solving a probably ill-conditioned linear operator equation, where the operator is not modeled by physical laws but is specified via training pairs (consisting of image…
Analysis of Generalized Iteratively Regularized Landweber Iterations driven by data
Andrea Aspri, Otmar Scherzer
We investigate generalized versions of the Iteratively Regularized Landweber Method, initially introduced in [Appl. Math. Optim., 38(1):45-68, 1998], to address linear and nonlinea…
Data driven reconstruction using frames and Riesz bases
Andrea Aspri, Leon Frischauf, Yury Korolev +1
We study the problem of regularization of inverse problems adopting a purely data driven approach, by using the similarity to the method of regularization by projection. We provide…
Data driven regularization by projection
Andrea Aspri, Yury Korolev, Otmar Scherzer
We study linear inverse problems under the premise that the forward operator is not at hand but given indirectly through some input-output training pairs. We demonstrate that regul…
A data-driven iteratively regularized Landweber iteration
Andrea Aspri, Sebastian Banert, Ozan Öktem +1
We derive and analyse a new variant of the iteratively regularized Landweber iteration, for solving linear and nonlinear ill-posed inverse problems. The method takes into account t…