research
∙
08/06/2023
PNN: From proximal algorithms to robust unfolded image denoising networks and Plug-and-Play methods
A common approach to solve inverse imaging problems relies on finding a ...
share
research
∙
04/21/2023
A Data-Driven Approach for Bayesian Uncertainty Quantification in Imaging
Uncertainty quantification in image restoration is a prominent challenge...
research
∙
01/06/2023
Uncertainty Quantification in CT pulmonary angiography
Computed tomography (CT) imaging of the thorax is widely used for the de...
research
∙
10/26/2022
A Variational Inequality Model for Learning Neural Networks
Neural networks have become ubiquitous tools for solving signal and imag...
research
∙
10/05/2022
A distributed Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems
Sampling-based algorithms are classical approaches to perform Bayesian i...
research
∙
03/02/2018