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20162023
most citedFaster Fundamental Graph Algorithms via Learned Predictions

4 citations · 16 across the 13 of their papers we have counts for

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cs.LG2022★ 3 cited

Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks

Anders Aamand, Justin Y. Chen, Piotr Indyk +5

Recent work shows that the expressive power of Graph Neural Networks (GNNs) in distinguishing non-isomorphic graphs is exactly the same as that of the Weisfeiler-Lehman (WL) graph…