Machine Learning for Gravitational Wave Data Analysis

7 oct. 2026, 09:00
45m
Dirac/RdC-Amphithéâtre (IP2I)

Dirac/RdC-Amphithéâtre

IP2I

160

Orateur

Antsa Rasamoela (L2I Toulouse, CNRS/IN2P3, Université de Toulouse)

Description

After a brief overview of Machine Learning fundamentals, this presentation offers a panorama of the main ML methods applied to gravitational-wave data processing: Simulation-Based Inference (SBI), transformer models, and diffusion models.

This panorama will be illustrated by the MANGO project, which is developing an ML framework to address the challenges posed by future detectors (Einstein Telescope and LISA), whose expected detection rates will exceed the capabilities of traditional MCMC methods.

The aim is to give the community a shared foundation of understanding, as an introduction to the more specific presentations of the day.

Auteur

Antsa Rasamoela (L2I Toulouse, CNRS/IN2P3, Université de Toulouse)

Documents de présentation

Aucun document.