In  the pipeline:

A. Blelly, H. Moutarde, J.BobinSparse data inpainting for the recovery of Galactic Binaries gravitational wave signals from gapped data, in prep., 2021.

R. Carloni Gertosio, J. Bobin, F. Acero, Semi-Blind Source Separation with Learned Physic-Driven Constraints, submitted, 2021.

J. Bobin, R. Carloni Gertosio, C. Bobin and C. Thiam, Non-linear interpolation learning for example-based inverse problem regularization, submitted, 2021.

J.Xu, J.Bobin, A. De Vismes, C.Bobin, Quantitative analysis of gamma-ray spectra with spectral unmixing: calibrations for HPGe detectors, submitted, 2021.

J.Xu, J.Bobin, A. De Vismes, C.Bobin, Analysis of gamma-ray spectra with spectral unmixing: determination of characteristic limits, submitted, 2021.

A. Picquenot, F. Acero, T. Holland-Ashford, L. A. Lopez, J. Bobin, Threedimensional morphological asymmetries in the ejecta of Cassiopeia A using a component separation method in X-rays, submitted to A&A, 2020.

Matrix factorization and blind source separation:

R.Carloni Gertosio, J.Bobin, Joint deconvolution and unsupervised source separation for data on the sphere, Signal Processing, in press, 2021.

C. Kervazo, T. Liaudat, J.Bobin, Faster and better sparse BSS through mini-batch optimization, accepted, 2020.

J.Bobin, I. El Hamzaoui, F.Acero, A.Picquenot, Sparse BSS from Poisson measurements, accepted, 2019.

C.Kervazo, J.Bobin, C.Chenot, F.Sureau, Use of PALM for l_1 Sparse Matrix Factorization: Difficulty and Rationalization of a Two-Step Approach, DSP, vol.97, 2020.

C. Kervazo, J.Bobin, C.Chenot, Blind separation of a large number of sparse sources, Signal Processing, vol. 150, 2018.

C.Chenot, J.Bobin, Blind Source Separation with outliers in transformed domains, SIAM Imag. Sciences, vol.11, issue 2,  2018.

C.Chenot, J.Bobin, Unsupervised separation of sparse sources in the presence of outliers, Signal Processing, vol. 138, 2017.

Signal processing for radio-astronomy:

S.Cunnington, M. Irfan, I. Carucci, A. Pourtsidou, J.Bobin, 21cm foregrounds and polarization leakage: cleaning and mitigation strategies, MNRAS, accepted, 2021.

I.Carucci, M.Irfan, J.Bobin, GMCA foreground cleaning for 21cm IM experiments, recovery of 21 cm intensity maps with sparse component separation, MNRAS accepted, 2020.

M. Jiang, J.Bobin, J-L Starck, Joint Multichannel Deconvolution and Blind Source Separation, SIAM Imaging Science, 10(4), 2017.

Signal processing for nuclear sciences:

C.Bobin, H.Paradis, J.Bobin, J.Bouchard, V.Lourenço, C.Thiam, R.André, L.Ferreux, A. de Vismes Ott, M. Thevenin, Spectral Unmixing Applied To Fast identification of gamma-emitting radionuclides using NaI(Tl) detectors, Applied Radiations and Isotopes, in press, 2020.

J. Xu, J.Bobin, A. de Vismes, C.Bobin, Sparse spectral unmixing for activity estimation in gamma-ray spectrometry, Applied Radiations and Isotopes, vol. 156, 2020.

J. Xu, J.Bobin, A. de Vismes, C.Bobin, Spectral unmixing for activity estimation in gamma-ray Spectrometry, in revision, 2019.

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, 625, 2019.

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, A&A, 623, A21, 2019.

M. Irfan, J.Bobin, Sparse estimation of model-based diffuse thermal dust emission, MNRAS, vol. 474, issue 4, 2018.

Analyzing weak lensing surveys:

A.Pujol, J.Bobin, F.Sureau, A.Guinot, M.Kilbinger, Shear measurement bias II: a fast machine learning calibration method, A&A, accepted, 2020.

A. Pujol, F. Sureau, J.Bobin, M. Gentile, F. Courbin, M.Kilbinger, Shear measurement bias. I: dependencies on methods, simulation parameters and measured parameters, A&A, accepted, 2020.

A. Pujol, M.Kilbinger, F. Sureau, J.Bobin, A highly precise shape-noise-free shear bias estimator, A&A, 621, A2, 2018.

Analyzing X-ray data:

A. Picquenot, F. Acero, J. Bobin, P. Maggi, J. Ballet, G.W. Pratt, A novel method for component separation of extended sources in X-ray astronomy, in revision, 2019.

Nuclear physics:

R.André, C.Bobin, J.Bobin, J.Xu, A.De Vismes, Metrological approach of γ-emitting radionuclides identification at low statistics: application of sparse spectral unmixing to scintillation detectors, in press, Metrologia, 2020.

C.Bobin, H.Paradis, J.Bobin, J.Bouchard, V.Lourenço, C.Thiam, R.André, L.Ferreux, A. de Vismes Ott, M. Thevenin, Spectral Unmixing Applied To Fast identification of gamma-emitting radionuclides using NaI(Tl) detectors, Applied Radiations and Isotopes, in press, 2020.

J. Xu, J.Bobin, A. de Vismes, C.Bobin, Sparse spectral unmixing for activity estimation in gamma-ray spectrometry, Applied Radiations and Isotopes, vol. 156, 2020.

Gravitational waves with LISA:

A.Blelly, J.Bobin, H.Moutarde, Sparsity Based Recovery of Galactic Binaries Gravitational Waves, accepted, Phys. Rev. D, 2020.

Sparse signal processing in optics:

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