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05/31/2023
Ambiguity in solving imaging inverse problems with deep learning based operators
In recent years, large convolutional neural networks have been widely us...
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11/24/2022
To be or not to be stable, that is the question: understanding neural networks for inverse problems
The solution of linear inverse problems arising, for example, in signal ...
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02/10/2021
Fast and stable deterministic approximation of general symmetric kernel matrices in high dimensions
Kernel methods are used frequently in various applications of machine le...
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01/04/2021
Minimizing L1 over L2 norms on the gradient
In this paper, we study the L1/L2 minimization on the gradient for imagi...
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05/31/2020
Limited-angle CT reconstruction via the L1/L2 minimization
In this paper, we consider minimizing the L1/L2 term on the gradient for...
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10/23/2019
Krylov Methods for Low-Rank Regularization
This paper introduces new solvers for the computation of low-rank approx...
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05/28/2017