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Found 3 papers, 1 papers with code
Learning a microlocal prior for limited-angle tomography
Limited-angle tomography is a highly ill-posed linear inverse problem.
Convex regularization in statistical inverse learning problems
We consider a statistical inverse learning problem, where the task is to estimate a function $f$ based on noisy point evaluations of $Af$, where $A$ is a linear operator.
Deep neural networks for inverse problems with pseudodifferential operators: an application to limited-angle tomography
We propose a novel convolutional neural network (CNN), called $\Psi$DONet, designed for learning pseudodifferential operators ($\Psi$DOs) in the context of linear inverse problems.
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