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SUMMARY:Scattering Transforms in astrophysics\, application to components 
 separation - Erwan Allys (ENS)
DTSTART:20231002T120000Z
DTEND:20231002T130000Z
UID:TALK205459@talks.cam.ac.uk
CONTACT:Inigo Zubeldia
DESCRIPTION:New statistical descriptions related to the so-called Scatteri
 ng Transform recently obtained attractive results for several astrophysica
 l applications. These statistics share ideas with convolutional neural net
 works\, but do not require to be learned\, allowing for very efficient cha
 racterization of non-Gaussian processes from a very small amount of data. 
 In this talk\, I will introduce these statistical descriptions\, and give 
 an overview of the different results they allowed to obtain recently. I wi
 ll focus on ongoing work on non-Gaussian modeling and component separation
  directly from observational data\, in the scientific context of CMB B-mod
 e detection beyond Galactic foregrounds.
LOCATION:CMS\, Pav. B\, CTC Common Room (B1.19) [Potter Room]
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