On the Impact of Phase Noise on Beamforming Performance for mmWave Massive MIMO Systems. - Baptiste Chatelier; Matthieu Crussière (WCNC, 2022)

Model-Based Deep Learning for Beam Prediction Based on a Channel Chart. - Taha Yassine; Baptiste Chatelier; Vincent Corlay; Matthieu Crussière; Stéphane Paquelet; Olav Tirkkonen; Luc Le Magoarou (ACSSC, 2023)

Influence of Dataset Parameters on the Performance of Direct UE Positioning via Deep Learning. - Baptiste Chatelier; Vincent Corlay; Cristina Ciochina; Fallou Coly; Julien Guillet (EuCNC/6G Summit, 2023)

Efficient Deep Unfolding for SISO-OFDM Channel Estimation. - Baptiste Chatelier; Luc Le Magoarou; Getachew Redieteab (ICC, 2023)

Model-based learning for location-to-channel mapping. - Baptiste Chatelier; Luc Le Magoarou; Vincent Corlay; Matthieu Crussière (CoRR, 2023)

CSI Compression Using Channel Charting. - Baptiste Chatelier; Vincent Corlay; Matthieu Crussière; Luc Le Magoarou (IEEECONF, 2024)

Model-Based Learning for Location-to-Channel Mapping. - Baptiste Chatelier; Luc Le Magoarou; Vincent Corlay; Matthieu Criissière (ICASSP, 2024)

Physically Parameterized Differentiable MUSIC for DoA Estimation with Uncalibrated Arrays. - Baptiste Chatelier; José Miguel Mateos-Ramos; Vincent Corlay; Christian Häger; Matthieu Crussière; Henk Wymeersch; Luc Le Magoarou (CoRR, 2024)

Model-Based Learning for Multi-Antenna Multi-Frequency Location-to-Channel Mapping. - Baptiste Chatelier; Vincent Corlay; Matthieu Crussière; Luc Le Magoarou (IEEE J. Sel. Top. Signal Process., 2025)

Model-based Neural Data Augmentation for sub-wavelength Radio Localization. - Baptiste Chatelier; Vincent Corlay; Musa Furkan Keskin; Matthieu Crussière; Henk Wymeersch; Luc Le Magoarou (CoRR, 2025)