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Certifying robustness of graph convolutional networks for node perturbation with polyhedra abstract interpretation.

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Title: Certifying robustness of graph convolutional networks for node perturbation with polyhedra abstract interpretation.
Authors: Chen, Boqi1, boqi.chen@mail.mcgill.ca, Marussy, Kristóf2, marussy@mit.bme.hu, Semeráth, Oszkár2, semerath@mit.bme.hu, Mussbacher, Gunter1, gunter.mussbacher@mcgill.ca, Varró, Dániel1,2,3, daniel.varro@liu.se
Source: Data Mining & Knowledge Discovery; Feb2026, Vol. 40 Issue 1, p1-42, 42p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 190293256
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Certifying robustness of graph convolutional networks for node perturbation with polyhedra abstract interpretation.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=190293256
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        Value: 10.1007/s10618-025-01180-w
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      – Code: eng
        Text: English
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              Text: Feb2026
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              Y: 2026
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