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    Perspectives on AI Architectures and Codesign for Earth System Predictability

    Source: Artificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 001
    Author:
    Mudunuru, Maruti K.
    ,
    Ang, James
    ,
    Halappanavar, Mahantesh
    ,
    Hammond, Simon D.
    ,
    Gokhale, Maya B.
    ,
    Hoe, James C.
    ,
    Krishna, Tushar
    ,
    Sreepathi, Sarat
    ,
    Norman, Matthew R.
    ,
    Peng, Ivy B.
    ,
    Jones, Philip W.
    DOI: 10.1175/AIES-D-23-0029.1
    Publisher: American Meteorological Society
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      Perspectives on AI Architectures and Codesign for Earth System Predictability

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4302204
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    • Artificial Intelligence for the Earth Systems

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    contributor authorMudunuru, Maruti K.
    contributor authorAng, James
    contributor authorHalappanavar, Mahantesh
    contributor authorHammond, Simon D.
    contributor authorGokhale, Maya B.
    contributor authorHoe, James C.
    contributor authorKrishna, Tushar
    contributor authorSreepathi, Sarat
    contributor authorNorman, Matthew R.
    contributor authorPeng, Ivy B.
    contributor authorJones, Philip W.
    date accessioned2024-12-24T15:20:39Z
    date available2024-12-24T15:20:39Z
    date copyright01 Jan. 2024
    date issued2024
    identifier otheraies-AIES-D-23-0029.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4302204
    languageEnglish
    publisherAmerican Meteorological Society
    titlePerspectives on AI Architectures and Codesign for Earth System Predictability
    typeJournal Paper
    journal volume3
    journal issue1
    journal titleArtificial Intelligence for the Earth Systems
    identifier doi10.1175/AIES-D-23-0029.1
    journal lastpagee230029
    treeArtificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 001
    contenttypeFulltext
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