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    Finding the Right XAI Method—A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science

    Source: Artificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 003
    Author:
    Bommer, Philine Lou
    ,
    Kretschmer, Marlene
    ,
    Hedström, Anna
    ,
    Bareeva, Dilyara
    ,
    Höhne, Marina M.-C.
    DOI: 10.1175/AIES-D-23-0074.1
    Publisher: American Meteorological Society
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      Finding the Right XAI Method—A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4299679
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    contributor authorBommer, Philine Lou
    contributor authorKretschmer, Marlene
    contributor authorHedström, Anna
    contributor authorBareeva, Dilyara
    contributor authorHöhne, Marina M.-C.
    date accessioned2024-12-24T13:49:38Z
    date available2024-12-24T13:49:38Z
    date copyright01 Jul. 2024
    date issued2024
    identifier otheraies-AIES-D-23-0074.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4299679
    languageEnglish
    publisherAmerican Meteorological Society
    titleFinding the Right XAI Method—A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science
    typeJournal Paper
    journal volume3
    journal issue3
    journal titleArtificial Intelligence for the Earth Systems
    identifier doi10.1175/AIES-D-23-0074.1
    journal lastpagee230074
    treeArtificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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