Inferring subglacial topography using physics informed machine learning constrained by two conservation laws.

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Title: Inferring subglacial topography using physics informed machine learning constrained by two conservation laws.
Authors: Krishna, Mansa1 (AUTHOR) mansa.krishna.gr@dartmouth.edu, Cheng, Gong1,2 (AUTHOR), Morlighem, Mathieu1 (AUTHOR)
Source: Cryosphere. 2026, Vol. 20 Issue 6, p3533-3558. 26p.
Database: Academic Search Ultimate
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  Data: Inferring subglacial topography using physics informed machine learning constrained by two conservation laws.
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  Data: <searchLink fieldCode="JN" term="%22Cryosphere%22">Cryosphere</searchLink>. 2026, Vol. 20 Issue 6, p3533-3558. 26p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=195125890
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      – Type: doi
        Value: 10.5194/tc-20-3533-2026
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      – Code: eng
        Text: English
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        StartPage: 3533
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      – TitleFull: Inferring subglacial topography using physics informed machine learning constrained by two conservation laws.
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            NameFull: Cheng, Gong
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              Text: 2026
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