NC-PDNet: a Density-Compensated Unrolled Network for 2D and 3D non-Cartesian MRI Reconstruction
Deep Learning has become a very promising avenue for magnetic resonance image (MRI) reconstruction.…
Category: Publications
All CosmoStat publications
Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction
Deep neural networks have recently been thoroughly investigated as a powerful tool for MRI…
Starlet l1-norm for weak lensing cosmology
Authors: Virginia Ajani, Jean-Luc Starck, Valeria Pettorino Journal: Astronomy & Astrophysics , Forthcoming…
State-of-the-art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge
Accelerating MRI scans is one of the principal outstanding problems in the MRI research…
Faster and better sparse blind source separation through mini-batch optimization
Sparse Blind Source Separation (sBSS) plays a key role in scientific domains as different…
Multi-CCD Point Spread Function Modelling
Context. Galaxy imaging surveys observe a vast number of objects that are affected by…
Probabilistic Mapping of Dark Matter by Neural Score Matching
The Dark Matter present in the Large-Scale Structure of the Universe is invisible, but…
XPDNet for MRI Reconstruction: an Application to the fastMRI 2020 Brain Challenge
We present a modular cross-domain neural network the XPDNet and its application to the…
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems
Deep neural networks have proven extremely efficient at solving a wide range of inverse…
Wavelets in the Deep Learning Era
Sparsity based methods, such as wavelets, have been state-of-the-art for more than 20 years…