The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison

We advocate for a new paradigm of cosmological likelihood-based inference, leveraging recent developments in machine learning and its underlying technology, to accelerate Bayesian inference in high-dimensional settings. Specifically, we combine (i) emulation, where a machine learning model is traine...

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Bibliographic Details
Main Authors: Davide Piras, Alicja Polanska, Alessio Spurio Mancini, Matthew A. Price, Jason D. McEwen
Format: Article
Language:English
Published: Maynooth Academic Publishing 2024-09-01
Series:The Open Journal of Astrophysics
Online Access:https://doi.org/10.33232/001c.123368
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