6.6k citations · 15.4k across the 73 of their papers we have counts for
74 papers
CHEX-MATE: A non-parametric deep learning technique to deproject and deconvolve galaxy cluster X-ray temperature profiles
A. Iqbal, G. W. Pratt, J. Bobin +21
Temperature profiles of the hot galaxy cluster intracluster medium (ICM) have a complex non-linear structure that traditional parametric modelling may fail to fully approximate. Fo…
Retrieving the 21-cm signal from the Epoch of Reionization with learnt Gaussian process kernels
Florent G. Mertens, Jérôme Bobin, Isabella P. Carucci
Direct detection of the Cosmic Dawn and Epoch of Reionization via the redshifted 21-cm line of neutral Hydrogen will have unprecedented implications for studying structure formatio…
Semi-Blind Source Separation with Learned Constraints
Rémi Carloni Gertosio, Jérôme Bobin, Fabio Acero
Blind source separation (BSS) algorithms are unsupervised methods, which are the cornerstone of hyperspectral data analysis by allowing for physically meaningful data decomposition…
Unrolling PALM for sparse semi-blind source separation
Mohammad Fahes, Christophe Kervazo, Jérôme Bobin +1
Sparse Blind Source Separation (BSS) has become a well established tool for a wide range of applications - for instance, in astrophysics and remote sensing. Classical sparse BSS me…
Sparse data inpainting for the recovery of Galactic-binary gravitational wave signals from gapped data
Aurore Blelly, Jérôme Bobin, Hervé Moutarde
The forthcoming space-based gravitational wave observatory LISA will open a new window for the measurement of galactic binaries, which will deliver unprecedented information about…
Three-dimensional morphological asymmetries in the ejecta of Cassiopeia A using a component separation method in X-rays
Adrien Picquenot, Fabio Acero, Tyler Holland-Ashford +2
Recent simulations have shown that asymmetries in the ejecta distribution of supernova remnants (SNR) can still reflect asymmetries from the initial supernova explosion. Thus, thei…