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  Causal hybrid modeling with double machine learning - Applications in carbon flux modeling

Cohrs, K.-H., Varando, G., Carvalhais, N., Reichstein, M., & Camps-Valls, G. (in press). Causal hybrid modeling with double machine learning - Applications in carbon flux modeling. Machine Learning: Science and Technology. doi:10.1088/2632-2153/ad5a60.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000F-78EE-F Version Permalink: https://hdl.handle.net/21.11116/0000-000F-78F2-9
Genre: Journal Article

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BGC4594pr.pdf (Preprint), 2MB
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https://doi.org/10.1088/2632-2153/ad5a60 (Publisher version)
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OA-Status:
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 Creators:
Cohrs, Kai-Hendrik, Author
Varando, Gherardo, Author
Carvalhais, Nuno1, Author           
Reichstein, Markus2, Author                 
Camps-Valls, Gustau, Author
Affiliations:
1Model-Data Integration, Dr. Nuno Carvalhais, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938310              
2Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139              

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 Dates: 2024-06-20
 Publication Status: Accepted / In Press
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC4594
DOI: 10.1088/2632-2153/ad5a60
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Project name : USMILE
Grant ID : 855187
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Machine Learning: Science and Technology
  Abbreviation : Mach. Learn.: Sci. Technol.
Source Genre: Journal
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Publ. Info: Bristol, UK : IOP Publishing
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 2632-2153
CoNE: https://pure.mpg.de/cone/journals/resource/2632-2153