27 citations · 69 across the 8 of their papers we have counts for
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cs.LG2024
Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach
Keke Huang, Wencai Cao, Hoang Ta +2
Graph Neural Networks (GNNs), known as spectral graph filters, find a wide range of applications in web networks. To bypass eigendecomposition, polynomial graph filters are propose…
cs.LG2024★ 27 cited
An end-to-end attention-based approach for learning on graphs
David Buterez, Jon Paul Janet, Dino Oglic +1
There has been a recent surge in transformer-based architectures for learning on graphs, mainly motivated by attention as an effective learning mechanism and the desire to supersed…