Paris workshop on Bayesian Deep Learning for Cosmology and Time Domain Astrophysics 3rd ed.

Session

Gravitational waves

May 21, 2025, 9:15 AM

Buffon Amphitheater (Université Paris Cité)

21. Simulation-based inference for gravitational-wave science

Konstantin Leyde (ICG Portsmouth)

5/21/25, 9:15 AM

Talk

Keynote + discussion

7. Non-Parametric Normalizing Flow Modeling of Binary Black Hole Populations for Unbiased Dark Siren Cosmology

LEONARDO Iampieri (Università di Roma La Sapienza, INFN,)

5/21/25, 11:10 AM

Cosmology

Talk

Gravitational-wave (GW) dark siren methods offer a powerful way to measure the expansion of the Universe without electromagnetic counterparts, but they rely critically on accurate models of the underlying binary black-hole (BBH) population. In fact, conventional parametric descriptions of BBH mass and redshift distributions can lead to significant biases in cosmological inferences when the...

23. GW parameters estimation with DNN

Edward Porter (APC/CNRS)

5/21/25, 11:30 AM

Talk

31. Disentangling the Gravitational Symphony: Machine Learning for LISA's Global Fit

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

5/21/25, 11:50 AM

Time Domain Astrophysics

Talk

The upcoming ESA mission LISA (Laser Interferometer Space Antenna), scheduled for launch in 2037, will usher in a transformative era in astrophysics by detecting gravitational waves from space. Unlike traditional observatories limited to the electromagnetic spectrum, LISA will directly probe the fabric of space-time, revealing a new and complex landscape of astrophysical signals from galactic...

33. The plug-and-play approach: learning the prior distribution from simulations. Application to gravitational wave reconstruction

Pierre PALUD (APC)

5/21/25, 12:10 PM

Talk

Current efforts in the LIGO-Virgo-KAGRA (LVK) collaboration focus on either parameter estimation from the observations of all available detectors, or denoising the measurements from a single detector. In this work, we address an intermediate task: reconstructing the original gravitational wave (GW) from the measurements of all available detectors. This inverse problem is ill-posed, and thus...