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Matrices efficientes pour le traitement du signal et l'apprentissage automatique. (Efficient matrices for signal processing and machine learning).. INSA de Rennes, France, (2016)mpNet: Variable Depth Unfolded Neural Network for Massive MIMO Channel Estimation., and . IEEE Trans. Wirel. Commun., 21 (7): 5703-5714 (2022)Massive MIMO channel estimation taking into account spherical waves., , and . CoRR, (2018)Are there approximate fast fourier transforms on graphs?, and . ICASSP, page 4811-4815. IEEE, (2016)On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels., , , , , , and . CoRR, (2023)Pervasive Artificial Intelligence in Next Generation Wireless: The Hexa-X Project Perspective., , , , , , , , , and 12 other author(s). AI6G@WCCI, volume 3189 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Model-Driven End-to-End Learning for Integrated Sensing and Communication., , , , and . ICC, page 5695-5700. IEEE, (2023)Efficient Deep Unfolding for SISO-OFDM Channel Estimation., , and . ICC, page 3450-3455. IEEE, (2023)Analyzing the approximation error of the fast graph Fourier transform., , and . ACSSC, page 45-49. IEEE, (2017)Exploiting the Massive MIMO Channel Structural Properties for Minimization of Channel Estimation Error and Training Overhead., , , , , , , and . IEEE Access, (2019)