Blind source separation :
The team work on sparse blind source separation has led to the implementation the following softwares:
GMCALab implements a simple but yet effective sparse BSS method (in Matlab)
pyGMCALab implements GMCA and AMCA (in Python)
nGMCALab extension of the GMCA algorithm for Non-negative Matrix Factorization (in Matlab and Python)
Component separation and Planck data processing :
LGMCA is a sparse component separation based on GMCA that is specifically tailored for the estimation of the CMB map from full-sky microwave surveys (WMAP and Planck).
Algorithm for solving sparse regression in signal processing :
Nesta is a sparse regression solver based on proximal algorithms and multi-step techniques in optimization.