Decidability of graph neural networks via logical characterizations

We present results concerning the expressiveness and decidability of a popular graph learning formalism, graph neural networks (GNNs), exploiting connections with logic. We use a family of recently-discovered decidable logics involving ``Presburger quantifiers''. We show how to use the...

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Bibliografski detalji
Glavni autori: Benedikt, M, Lu, C-H, Motik, B, Tan, T
Format: Conference item
Jezik:English
Izdano: Lipics 2024