Résumé / Abstract Journal-club_Univers

Séminaire Univers /
Seminar Universe

« A new vocabulary for patterns and its cosmological applications, or, CNN without training  »

Sihao Cheng
Dept. Physics Astron., John Hopkins Univ. (Baltimore, Maryland, Etats-Unis)

Textures and patterns are ubiquitous in astronomical data but challenging for quantitative analysis. I will present a new tool, called the “scattering transform”. It borrows ideas from convolutional neural nets (CNNs) while sharing advantages of traditional statistical estimators. As an example, I will show its application to weak lensing maps for constraining cosmological parameters and show that it outperforms classic statistics. It is a powerful new approach in astrophysics and beyond.

mardi 1 décembre 2020 - 14:00
Institut d'Astrophysique de Paris
Pages web du séminaire / Seminar's webpage