1 citations · 2 across the 13 of their papers we have counts for
4 papers · 1 filter
Gradient Step Plug-and-Play Model for Dental Cone-Beam CT Reconstruction
Idris Tatachak, Luis Kabongo, Nicolas Papadakis +2
The goal of this work is to reduce the effect of photon noise in dental cone-beam CT reconstruction. We consider an inverse problem formulation and develop a databased prior. To th…
i-DEQ: A stable inertial deep equilibrium model for image restoration
Antonin Clerc, Marien Renaud, Baudouin Denis De Seneville +2
Deep Equilibrium Models (DEQs) are an established framework for image restoration that learn a problem-adapted regularization by solving a fixed-point (i.e. equilibrium) problem. W…
On the Convergence of Proximal Algorithms for Weakly-convex Min-max Optimization
Guido Tapia-Riera, Camille Castera, Nicolas Papadakis
We study alternating first-order algorithms with no inner loops for solving nonconvex-strongly concave min-max problems. We show the convergence of the alternating gradient descent…
Reinterpreting EMML as Mirror Descent for Constrained Maximum Likelihood Estimation
Antonin Clerc, Ségolène Martin, Nicolas Papadakis +1
The Expectation--Maximization Maximum Likelihood (EMML) algorithm belongs to the Expectation--Maximization family and is widely used for image reconstruction problems under Poisson…