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Analyzing the effect of residual connections to oversmoothing in graph neural networks.

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Title: Analyzing the effect of residual connections to oversmoothing in graph neural networks.
Authors: Kelesis, Dimitrios1,2, dkelesis@iit.demokritos.gr, Fotakis, Dimitris1,3, fotakis@cs.ntua.gr, Paliouras, Georgios2, paliourg@iit.demokritos.gr
Source: Machine Learning; Aug2025, Vol. 114 Issue 8, p1-25, 25p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 186612625
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Analyzing the effect of residual connections to oversmoothing in graph neural networks.
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  Data: <searchLink fieldCode="AU" term="%22Kelesis%2C+Dimitrios%22">Kelesis, Dimitrios</searchLink><relatesTo>1,2</relatesTo>, <i>dkelesis@iit.demokritos.gr</i><br /><searchLink fieldCode="AU" term="%22Fotakis%2C+Dimitris%22">Fotakis, Dimitris</searchLink><relatesTo>1,3</relatesTo>, <i>fotakis@cs.ntua.gr</i><br /><searchLink fieldCode="AU" term="%22Paliouras%2C+Georgios%22">Paliouras, Georgios</searchLink><relatesTo>2</relatesTo>, <i>paliourg@iit.demokritos.gr</i>
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  Data: <searchLink fieldCode="JN" term="%22Machine+Learning%22">Machine Learning</searchLink>; Aug2025, Vol. 114 Issue 8, p1-25, 25p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=186612625
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1007/s10994-025-06822-0
    Languages:
      – Code: eng
        Text: English
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        PageCount: 25
        StartPage: 1
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      – TitleFull: Analyzing the effect of residual connections to oversmoothing in graph neural networks.
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            NameFull: Kelesis, Dimitrios
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            NameFull: Fotakis, Dimitris
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            NameFull: Paliouras, Georgios
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            – D: 01
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
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              Value: 114
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              Value: 8
          Titles:
            – TitleFull: Machine Learning
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