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  Neural networks for reconstruction and uncertainty quantification of fast-ion phase-space distributions using FILD and INPA measurements

Schmidt, B. S., Rueda-Rueda, J., Galdon-Quíroga, J., Garcia-Munoz, M., Schneider, P. A., Salewski, M., et al. (2025). Neural networks for reconstruction and uncertainty quantification of fast-ion phase-space distributions using FILD and INPA measurements. Nuclear Fusion, 65: 016025. doi:10.1088/1741-4326/ad93e6.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0010-4C36-D Version Permalink: https://hdl.handle.net/21.11116/0000-0010-4C37-C
Genre: Journal Article

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schmidt_neural.pdf (Supplementary material), 5MB
 
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https://dx.doi.org/10.1088/1741-4326/ad93e6 (Publisher version)
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Open Access
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 Creators:
Schmidt, B. S.1, Author
Rueda-Rueda, J.1, Author
Galdon-Quíroga, J.1, Author
Garcia-Munoz, M.1, Author
Schneider, P. A.2, Author                 
Salewski, M., Author
ASDEX Upgrade Team, Max Planck Institute for Plasma Physics, Max Planck Society, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Tokamak Scenario Development (E1), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856321              

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Language(s): eng - English
 Dates: 20242025
 Publication Status: Issued
 Pages: 19 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1741-4326/ad93e6
 Degree: -

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Project name : Euratom Research and Training Programme 2021-2027 – EUROfusion
Grant ID : 101052200
Funding program : Horizon Europe (HE)
Funding organization : European Commission (EC)

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Title: Nuclear Fusion
Source Genre: Journal
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Publ. Info: Bristol; Vienna : IOP Publishing; IAEA
Pages: - Volume / Issue: 65 Sequence Number: 016025 Start / End Page: - Identifier: ISSN: 0029-5515
CoNE: https://pure.mpg.de/cone/journals/resource/991042749627140