19 citations · 40 across the 12 of their papers we have counts for
4 papers · 1 filter
Convergent Plug-and-Play Image Restoration with Annealed Noise Levels
Samuel Hurault
Plug-and-Play (PnP) methods solve imaging inverse problems by incorporating deep denoisers into iterative optimization algorithms. Although practical implementations often decrease…
Optimization with First Order Algorithms
Charles Dossal, Samuel Hurault, Nicolas Papadakis
These notes focus on the minimization of convex functionals using first-order optimization methods, which are fundamental in many areas of applied mathematics and engineering. The…
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter
Samuel Hurault, Antonin Chambolle, Arthur Leclaire +1
In this work, we present new proofs of convergence for Plug-and-Play (PnP) algorithms. PnP methods are efficient iterative algorithms for solving image inverse problems where regul…
Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization
Samuel Hurault, Arthur Leclaire, Nicolas Papadakis
Plug-and-Play (PnP) methods solve ill-posed inverse problems through iterative proximal algorithms by replacing a proximal operator by a denoising operation. When applied with deep…