Extrapolated plug-and-play three-operator splitting methods for nonconvex optimization with applications to image restoration
This paper investigates the convergence properties and applications of the three-operator
splitting method, also known as the Davis–Yin splitting (DYS) method, integrated with …
splitting method, also known as the Davis–Yin splitting (DYS) method, integrated with …
Constrained Plug-and-Play Priors for Image Restoration
A Benfenati, P Cascarano - Journal of Imaging, 2024 - mdpi.com
The Plug-and-Play framework has demonstrated that a denoiser can implicitly serve as the
image prior for model-based methods for solving various inverse problems such as image …
image prior for model-based methods for solving various inverse problems such as image …
Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging
Imaging tasks are typically addressed using a structured optimization framework. This paper
investigates a class of algorithms for difference-of-convex (DC) structured optimization …
investigates a class of algorithms for difference-of-convex (DC) structured optimization …
Learning truly monotone operators with applications to nonlinear inverse problems
This article introduces a novel approach to learning monotone neural networks through a
newly defined penalization loss. The proposed method is particularly effective in solving …
newly defined penalization loss. The proposed method is particularly effective in solving …
Compressive Recovery of Sparse Precision Matrices
We consider the problem of learning a graph modeling the statistical relations of the $ d $
variables of a dataset with $ n $ samples $ X\in\mathbb {R}^{n\times d} $. Standard …
variables of a dataset with $ n $ samples $ X\in\mathbb {R}^{n\times d} $. Standard …
Convergent plug-and-play methods for image inverse problems with explicit and nonconvex deep regularization
S Hurault - 2023 - theses.hal.science
Plug-and-play methods constitute a class of iterative algorithms for imaging inverse
problems where regularization is performed by an off-the-shelf Gaussian denoiser. These …
problems where regularization is performed by an off-the-shelf Gaussian denoiser. These …
Integrating variational and learning models for imaging inverse problems
A Sebastiani - 2024 - amsdottorato.unibo.it
Imaging inverse problems are fundamental in various fields like diagnostic medicine and
manufacturing engineering. Current methods for reconstruction can be divided into …
manufacturing engineering. Current methods for reconstruction can be divided into …