Unifying approach to uniform expressivity of graph neural networks | ScienceToStartup | ScienceToStartup

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References (19)

[1]

On the Expressive Power of Subgraph Graph Neural Networks for Graphs with Bounded Cycles

2025Ziang Chen, Qiao Zhang et al.

[2]

Halting Recurrent GNNs and the Graded μ-Calculus

2025Jeroen Bollen, Jan Van den Bussche et al.

[3]

Bridging Max Graph Neural Networks and Datalog with Negation

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"Generalize GNN architectures for enhanced expressivity using template embeddings and graded modal logic."

Graph Neural Networks•Score: 2•View PDF ↗

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Unifying approach to uniform expressivity of graph neural networks

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References (19)

Founder's Pitch

"Generalize GNN architectures for enhanced expressivity using template embeddings and graded modal logic."

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