Wavelets in the Deep Learning Era. - Zaccharie Ramzi; Jean-Luc Starck; Thomas Moreau 001; Philippe Ciuciu (EUSIPCO, 2020)

Benchmarking Deep Nets MRI Reconstruction Models on the Fastmri Publicly Available Dataset. - Zaccharie Ramzi; Philippe Ciuciu; Jean-Luc Starck (ISBI, 2020)

PySAP: Python Sparse Data Analysis Package for multidisciplinary image processing. - Samuel Farrens; Antoine Grigis; Loubna El Gueddari; Zaccharie Ramzi; Chaithya G. R.; Sophie Starck; Benoît Sarthou; Hamza Cherkaoui; Philippe Ciuciu; Jean-Luc Starck (Astron. Comput., 2020)

XPDNet for MRI Reconstruction: an Application to the fastMRI 2020 Brain Challenge. - Zaccharie Ramzi; Philippe Ciuciu; Jean-Luc Starck (CoRR, 2020)

Denoising Score-Matching for Uncertainty Quantification in Inverse Problems. - Zaccharie Ramzi; Benjamin Remy; François Lanusse; Jean-Luc Starck; Philippe Ciuciu (CoRR, 2020)

State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge. - Matthew J. Muckley; Bruno Riemenschneider; Alireza Radmanesh; Sunwoo Kim; Geunu Jeong; Jingyu Ko; Yohan Jun; Hyungseob Shin; Dosik Hwang; Mahmoud Mostapha; Simon Arberet; Dominik Nickel; et al. (CoRR, 2020)

Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction. - Chaithya G. R.; Zaccharie Ramzi; Philippe Ciuciu (EUSIPCO, 2021)

Density Compensated Unrolled Networks For Non-Cartesian MRI Reconstruction. - Zaccharie Ramzi; Jean-Luc Starck; Philippe Ciuciu (ISBI, 2021)

Is good old GRAPPA dead? - Zaccharie Ramzi; Alexandre Vignaud; Jean-Luc Starck; Philippe Ciuciu (CoRR, 2021)

Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. - Matthew J. Muckley; Bruno Riemenschneider; Alireza Radmanesh; Sunwoo Kim; Geunu Jeong; Jingyu Ko; Yohan Jun; Hyungseob Shin; Dosik Hwang; Mahmoud Mostapha; Simon Arberet; Dominik Nickel; et al. (IEEE Trans. Medical Imaging, 2021)

SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models. - Zaccharie Ramzi; Florian Mannel; Shaojie Bai; Jean-Luc Starck; Philippe Ciuciu; Thomas Moreau 001 (ICLR, 2022)

MC-PDNet: Deep Unrolled Neural Network For Multi-Contrast Mr Image Reconstruction From Undersampled K-Space Data. - Kumari Pooja; Zaccharie Ramzi; Chaithya G. R.; Philippe Ciuciu (ISBI, 2022)

Hybrid Learning of Non-Cartesian K-Space Trajectory and Mr Image Reconstruction Networks. - Chaithya G. R.; Zaccharie Ramzi; Philippe Ciuciu (ISBI, 2022)

Benchopt: Reproducible, efficient and collaborative optimization benchmarks. - Thomas Moreau 001; Mathurin Massias; Alexandre Gramfort; Pierre Ablin; Pierre-Antoine Bannier; Benjamin Charlier; Mathieu Dagréou; Tom Dupré la Tour; Ghislain Durif; Cássio F. Dantas; Quentin Klopfenstein; Johan Larsson 002; et al. (NeurIPS, 2022)

NC-PDNet: A Density-Compensated Unrolled Network for 2D and 3D Non-Cartesian MRI Reconstruction. - Zaccharie Ramzi; Chaithya G. R.; Jean-Luc Starck; Philippe Ciuciu (IEEE Trans. Medical Imaging, 2022)

Advanced deep neural networks for MRI image reconstruction from highly undersampled data in challenging acquisition settings. (Réseaux de neurones profonds avancés pour la reconstruction d'images IRM à partir de données fortement sous-échantillonnées dans des contextes d'acquisition complexes). - Zaccharie Ramzi (2022)

Test like you Train in Implicit Deep Learning. - Zaccharie Ramzi; Pierre Ablin; Gabriel Peyré; Thomas Moreau 001 (CoRR, 2023)

Wavelets in the Deep Learning Era. - Zaccharie Ramzi; Kevin Michalewicz; Jean-Luc Starck; Thomas Moreau 001; Philippe Ciuciu (J. Math. Imaging Vis., 2023)