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  21-cm signal from the Epoch of Reionization: a machine learning upgrade to foreground removal with Gaussian process regression

Acharya, A., Mertens, F., Ciardi, B., Ghara, R., Koopmans, L. V. E., Giri, S. K., et al. (2024). 21-cm signal from the Epoch of Reionization: a machine learning upgrade to foreground removal with Gaussian process regression. Monthly Notices of the Royal Astronomical Society, 527(3), 7835-7846. doi:10.1093/mnras/stad3701.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000E-771D-D Version Permalink: https://hdl.handle.net/21.11116/0000-000E-771E-C
Genre: Journal Article

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 Creators:
Acharya, Anshuman1, Author           
Mertens, Florent, Author
Ciardi, Benedetta1, Author           
Ghara, Raghunath, Author
Koopmans, Léon V. E., Author
Giri, Sambit K., Author
Hothi, Ian, Author
Ma, Qing-Bo, Author
Mellema, Garrelt, Author
Munshi, Satyapan, Author
Affiliations:
1Computational Structure Formation, MPI for Astrophysics, Max Planck Society, ou_2205642              

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Language(s): eng - English
 Dates: 2023-11-292024-01
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1093/mnras/stad3701
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Title: Monthly Notices of the Royal Astronomical Society
  Other : Mon. Not. R. Astron. Soc.
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 527 (3) Sequence Number: - Start / End Page: 7835 - 7846 Identifier: ISSN: 1365-8711
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000024150