Responsible Machine Learning in Heliophysics

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dc.contributor.authorNarock, Ayris
dc.contributor.authorBard, Christopher
dc.contributor.authorThompson, Barbara J.
dc.contributor.authorHalford, Alexa
dc.contributor.authorMcGranaghan, Ryan
dc.contributor.authorda Silva, Daniel
dc.contributor.authorKosar, Burcu
dc.contributor.authorShumko, Mykhaylo
dc.date.accessioned2023-01-04T23:18:16Z
dc.date.available2023-01-04T23:18:16Z
dc.date.issued2023-07-31
dc.description.abstractMachine learning has become embedded in the field of Heliophysics. Ethical and responsible use of these methods encompasses many aspects that create necessary additional burden to the individual researcher and the research community as a whole. Sustained financial and infrastructural support from affiliated agencies and institutions is needed in addition to community-based governance strategies.en_US
dc.description.urihttps://baas.aas.org/pub/2023n3i288/release/1en_US
dc.format.extent8 pagesen_US
dc.genrejournal articlesen_US
dc.identifierhttps://doi.org/10.3847/25c2cfeb.ce7c61a6
dc.identifier.citationNarock, Ayris, Chris Bard, Barbara Thompson, Alexa Halford, Ryan McGranaghan, Daniel da Silva, Burcu Kosar, and Mykhaylo Shumko. “Responsible Machine Learning in Heliophysics.” Bulletin of the AAS 55, no. 3 (July 31, 2023). https://doi.org/10.3847/25c2cfeb.ce7c61a6. en_US
dc.identifier.urihttp://hdl.handle.net/11603/26550
dc.language.isoen_USen_US
dc.publisherAAS
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Goddard Planetary Heliophysics Institute (GPHI)
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleResponsible Machine Learning in Heliophysicsen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0001-7537-3539en_US

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