Matrix factorization and blind source separation:

C. Kervazo, J.Bobin, C.Chenot, F.Sureau, Heuristics for Efficient Sparse Blind Source Separation, in prep, 2018.

C. Kervazo, J.Bobin, C.Chenot, Blind separation of a large number of sparse sources, accepted, 2017.

C.Chenot, J.Bobin, , SIAM Imaging Science, Blind Source Separation with outliers in transformed domains, in press, 2017.

C.Chenot, J.Bobin, Unsupervised separation of sparse sources in the presence of outliers, Signal Processing, in press, 2017.

 

Signal processing for radio-astronomy:

M. Jiang, J.Bobin, J-L Starck, Joint Multichannel Deconvolution and Blind Source Separation, SIAM Imaging Science, in press, 2017.

 

Machine learning and its applications:

M. Frontera-Pons, B. Moraes, F.Sureau, J.Bobin, F.Abdalla, Representation learning for automated spectroscopic redshift estimation, A&A, submitted, 2018.

M. Frontera-Pons, F.Sureau, J.Bobin, E Le Floc’h, Unsupervised feature learning for galaxy SEDs with denoising autoencoders, A&A, 603, A60, 2017.

 

A new look at the Planck data:

M. Irfan, J.Bobin, M-A Miville-Deschênes, I. Grenier Determining thermal dust emission from Planck HFI data using a sparse, parametric technique, in prep., 2018.

M. Irfan, J.Bobin, Sparse estimation of model-based diffuse thermal dust emission, MNRAS, accepted, 2017.

 

Analyzing weak lensing surveys:

A. Pujol, M.Kilbinger, F. Sureau, J.Bobin, A highly precise shape-noise-free shear bias estimator, A&A, in revision, 2018.

A. Pujol, F. Sureau, J.Bobin, M. Gentile, F. Courbin, M.Kilbinger, Shear measurement bias: dependencies on methods, simulation parameters and measured parameters, A&A, in revision, 2017.

 

Sparse signal processing in optics:

J.Fade, E. Perrotin, J.Bobin, Two-pixel polarimetric camera by compressive sensing, Applied Optics, accepted, 2017.