research
∙
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...
share
research
∙
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 ...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
10/23/2019
Krylov Methods for Low-Rank Regularization
This paper introduces new solvers for the computation of low-rank approx...
research
∙
05/28/2017
