Leveraging Low-Rank and H2 Shared Bases in the Solution of Large Scale Linear Inverse Problems with Applications to Seismic Data Processing.

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Title: Leveraging Low-Rank and H2 Shared Bases in the Solution of Large Scale Linear Inverse Problems with Applications to Seismic Data Processing.
Authors: Sushnikova, Daria1, daria.sushnikova@gmail.com, Ravasi, Matteo1,2, mravasi@shearwatergeo.com, Keyes, David1
Source: Journal of Scientific Computing; Oct2025, Vol. 105 Issue 1, p1-22, 22p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 187802886
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Leveraging Low-Rank and H2 Shared Bases in the Solution of Large Scale Linear Inverse Problems with Applications to Seismic Data Processing.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Scientific+Computing%22">Journal of Scientific Computing</searchLink>; Oct2025, Vol. 105 Issue 1, p1-22, 22p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=187802886
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s10915-025-03045-2
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      – Code: eng
        Text: English
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        PageCount: 22
        StartPage: 1
    Titles:
      – TitleFull: Leveraging Low-Rank and H2 Shared Bases in the Solution of Large Scale Linear Inverse Problems with Applications to Seismic Data Processing.
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            NameFull: Sushnikova, Daria
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            NameFull: Ravasi, Matteo
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            NameFull: Keyes, David
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            – D: 01
              M: 10
              Text: Oct2025
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              Y: 2025
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