Uncertainties for large scale deep learning-based image reconstruction
Position: PhD Deadline: 15/04/2021 Contact: Jean-Luc Starck Details about this position are provided in…
Author: Jean-Luc Starck
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…
Benchmarking Deep Nets MRI Reconstruction Models on the FastMRI Publicly Available Dataset
The MRI reconstruction field lacked a proper data set that allowed for reproducible…
Benchmarking proximal methods acceleration enhancements for CS-acquired MR image analysis reconstruction
Reference: Z. Ramzi, P. Ciuciu and J.-L. Starck. “Benchmarking proximal methods acceleration enhancements for CS-acquired MR image…
Euclid: impact of nonlinear prescriptions on cosmological parameter estimation from weak lensing cosmic shear
Authors: Martinelli, M.;Tutusaus, I.;Archidiacono, M.;Camera, S.;Cardone, V. F.;Clesse, S.;Casas, S.;Casarini, L.;Mota, D. F.;Hoekstra,…