Speaker
Thomas SAINRAT
Description
Plug-and-Play methods have been introduced as a generalization of
variational-based regularization techniques for image-related inverse
problems. They combine a Gaussian denoising task with a tractable
likelihood to achieve state-of-the-art image reconstruction. The
denoising component is flexible and typically implemented using neural
networks. We present an application of this method to reconstruct the
polarization of gravitational waves from detector data. A
proof-of-concept is demonstrated for compact binary coalescences, where
polarization evolution serves as a signature of relativistic precession.
Authors
Dr
Eric Chassande-Mottin
Thomas SAINRAT