9–12 Sept 2024
Imperial College London
Europe/London timezone

Bayesian evidence estimation with normalizing flows

Not scheduled
20m
Lecture Theatre 2, Blackett Laboratory (Imperial College London)

Lecture Theatre 2, Blackett Laboratory

Imperial College London

Poster

Speaker

Rahul Srinivasan

Description

Using ${\it floZ}$, an improved Bayesian evidence (and its numerical uncertainty) estimation method based on normalizing flows, we estimate the Bayes factor in favor of gravitational wave overtones in the ringdown of the first detection. We find good agreement with nested sampling. Provided representative samples from the target posterior are available, our method is more robust to posterior distributions with sharp features, especially in higher dimensions. I propose a metric to evaluate the flow training completion using the latent space map of the posterior samples. Finally, I introduce a nested flow technique for improved density estimation.

Primary Field of Research Astro/Cosmo

Author

Co-authors

Enrico Barausse Dr Marco Crisostomi (California Institute of Technology, USA) Roberto Trotta

Presentation materials

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