activity
20142024
most citedThe LOFAR Two Meter Sky Survey: Deep Fields, I -- Direction-dependent calibration and imaging

248 citations · 771 across the 28 of their papers we have counts for

collaborators

29 papers

astro-ph.IM2024★ 4 cited

Africanus III. pfb-imaging -- a flexible radio interferometric imaging suite

Hertzog L. Bester, Jonathan S. Kenyon, Audrey Repetti +8

The popularity of the CLEAN algorithm in radio interferometric imaging stems from its maturity, speed, and robustness. While many alternatives have been proposed in the literature,…

math.OC2024

Learning truly monotone operators with applications to nonlinear inverse problems

Younes Belkouchi, Jean-Christophe Pesquet, Audrey Repetti +1

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 cl…

math.OC2024

A multilevel framework for accelerating uSARA in radio-interferometric imaging

Guillaume Lauga, Audrey Repetti, Elisa Riccietti +3

This paper presents a multilevel algorithm specifically designed for radio-interferometric imaging in astronomy. The proposed algorithm is used to solve the uSARA (unconstrained Sp…

cs.CV2023★ 1 cited

Unfolded proximal neural networks for robust image Gaussian denoising

Hoang Trieu Vy Le, Audrey Repetti, Nelly Pustelnik

A common approach to solve inverse imaging problems relies on finding a maximum a posteriori (MAP) estimate of the original unknown image, by solving a minimization problem. In thi…

math.OC2023

A new non-convex framework to improve asymptotical knowledge on generic stochastic gradient descent

Jean-Baptiste Fest, Audrey Repetti, Emilie Chouzenoux

Stochastic gradient optimization methods are broadly used to minimize non-convex smooth objective functions, for instance when training deep neural networks. However, theoretical g…

eess.IV2023

A primal-dual data-driven method for computational optical imaging with a photonic lantern

Carlos Santos Garcia, Mathilde Larchevêque, Solal O'Sullivan +4

Optical fibres aim to image in-vivo biological processes. In this context, high spatial resolution and stability to fibre movements are key to enable decision-making processes (e.g…