Laboratoire d’Études du Rayonnement et de la Matière en Astrophysique et Atmosphères

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Stages Master 1

par Valerie Audon - publié le , mis à jour le

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Séminaires à venir

Vendredi 2 mars 2018, 14h00
Salle de l'atelier, Paris
Machine Learning in Astronomy
University College London
résumé :
Astrophysics, High Energy Physics and other Physical sciences are undergoing an ‘industrial revolution’ with huge data sets and complex models to describe them. For example, galaxy surveys (e.g. DES, DESI, LSST, Euclid, SKA) will catalog billions of galaxies over the coming decade. Similarly, Particle Physics experiments, e.g. at CERN, generate gigantic data sets. Such data sets call for entirely new approaches for data analysis. Fortunately, powerful ‘Machine Learning’ methods have been invented by statisticians and computer scientists and they are widely applied across science, technology and medicine.
The talk will illustrate examples such as classification of galaxies and supernovae, estimating galaxy redshifts and other properties from their colours, and deriving the mass of the Local Group.
We shall also discuss programmes for training of the next generation of data scientists in connection with industry partners, e.g. UCL’s Centre for Doctoral Training In Data Intensive Science http://www.hep.ucl.ac.uk/cdt-dis/
Vendredi 23 mars 2018, 14h00
Salle de l'atelier, Paris
Charlène Lefèvre
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