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cs.AI2026
The Correspondence Between Bounded Graph Neural Networks and Fragments of First-Order Logic
Bernardo Cuenca Grau, Eva Feng, PrzemysÅaw Andrzej WaÅÄga
Graph Neural Networks (GNNs) address two key challenges in applying deep learning to graph-structured data: they handle varying size input graphs and ensure invariance under graph…
cs.AI2025
From Neural Networks to Logical Theories: The Correspondence between Fibring Modal Logics and Fibring Neural Networks
Ouns El Harzli, Bernardo Cuenca Grau, Artur d'Avila Garcez +2
Fibring of modal logics is a well-established formalism for combining countable families of modal logics into a single fibred language with common semantics, characterized by fibre…