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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 ...
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03/17/2022
Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers
Monitoring the Covid19 pandemic constitutes a critical societal stake th...
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02/20/2022
Alternative design of DeepPDNet in the context of image restoration
This work designs an image restoration deep network relying on unfolded ...
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02/11/2022
Temporal evolution of the Covid19 pandemic reproduction number: Estimations from proximal optimization to Monte Carlo sampling
Monitoring the evolution of the Covid19 pandemic constitutes a critical ...
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09/20/2021
Nonsmooth convex optimization to estimate the Covid-19 reproduction number space-time evolution with robustness against low quality data
Daily pandemic surveillance, often achieved through the estimation of th...
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09/08/2020
Primal-dual splitting scheme with backtracking for handling with epigraphic constraint and sparse analysis regularization
The convergence of many proximal algorithms involving a gradient descent...
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07/02/2020
A deep primal-dual proximal network for image restoration
Image restoration remains a challenging task in image processing. Numero...
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04/20/2020
Automated data-driven selection of the hyperparameters for Total-Variation based texture segmentation
Penalized Least Squares are widely used in signal and image processing. ...
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10/31/2019
Solving NMF with smoothness and sparsity constraints using PALM
Non-negative matrix factorization is a problem of dimensionality reducti...
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08/27/2016
Bayesian selection for the l2-Potts model regularization parameter: 1D piecewise constant signal denoising
Piecewise constant denoising can be solved either by deterministic optim...
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04/22/2015