activity
20142024
most citedLearning computationally efficient dictionaries and their implementation as fast transforms

7 citations · 13 across the 6 of their papers we have counts for

collaborators

6 papers

physics.optics2024

Optimal blind focusing on perturbation-inducing targets in sub-unitary complex media

Jérôme Sol, Luc Le Magoarou, Philipp del Hougne

The scattering of waves in a complex medium is perturbed by polarizability changes or motion of embedded targets. These perturbations could serve as perfectly non-invasive guidesta…

eess.SP2023

Model-based Deep Learning for High-Dimensional Periodic Structures

Lucas Polo-López, Luc Le Magoarou, Romain Contreres +1

This work presents a deep learning surrogate model for the fast simulation of high-dimensional frequency selective surfaces. We consider unit-cells which are built as multiple conc…

cs.AI2023

Model-based learning for location-to-channel mapping

Baptiste Chatelier, Luc Le Magoarou, Vincent Corlay +1

Modern communication systems rely on accurate channel estimation to achieve efficient and reliable transmission of information. As the communication channel response is highly rela…

eess.SP20236 cited

Experimentally realized physical-model-based wave control in metasurface-programmable complex media

Jérôme Sol, Hugo Prod'homme, Luc Le Magoarou +1

The reconfigurability of radio environments with programmable metasurfaces is considered a key feature of next-generation wireless networks. Identifying suitable metasurface config…

cs.IT2021

Deep learning for location based beamforming with NLOS channels

Luc Le Magoarou, Taha Yassine, Stéphane Paquelet +1

Massive MIMO systems are highly efficient but critically rely on accurate channel state information (CSI) at the base station in order to determine appropriate precoders. CSI acqui…

cs.LG20147 cited

Learning computationally efficient dictionaries and their implementation as fast transforms

Luc Le Magoarou, Rémi Gribonval

Dictionary learning is a branch of signal processing and machine learning that aims at finding a frame (called dictionary) in which some training data admits a sparse representatio…