Model-independent reconstruction of the interacting dark energy kernel: Binned and Gaussian process

Escamilla, L.A., Akarsu, Ö, Di Valentino, E. orcid.org/0000-0001-8408-6961 et al. (1 more author) (2023) Model-independent reconstruction of the interacting dark energy kernel: Binned and Gaussian process. Journal of Cosmology and Astroparticle Physics, 2023 (11). 051. ISSN 1475-7516

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Copyright, Publisher and Additional Information: © 2023 The Author(s). Published by IOP Publishing Ltd on behalf of Sissa Medialab. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence (http://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Keywords: Bayesian reasoning; dark energy theory; Machine learning
Dates:
  • Submitted: 26 May 2023
  • Accepted: 19 September 2023
  • Published (online): 13 November 2023
  • Published: 1 November 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 23 Nov 2023 15:31
Last Modified: 23 Nov 2023 15:31
Status: Published
Publisher: IOP Publishing
Refereed: Yes
Identification Number: https://doi.org/10.1088/1475-7516/2023/11/051

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