Expander graph propagation
Deploying graph neural networks (GNNs) on whole-graph classification or regression tasks is known to be challenging: it often requires computing node features that are mindful of both local interactions in their neighbourhood and the global context of the graph structure. GNN architectures that navi...
Main Authors: | Deac, A, Lackenby, M, Veličković, P |
---|---|
Format: | Conference item |
Jezik: | English |
Izdano: |
Journal of Machine Learning Research
2022
|
Podobne knjige/članki
-
Expanders, rank and graphs of groups
od: Lackenby, M
Izdano: (2004) -
How does over-squashing affect the power of GNNs?
od: Di Giovanni, F, et al.
Izdano: (2024) -
Expander graphs
od: Kahale, Nabil
Izdano: (2005) -
Parameterized counting and Cayley graph expanders
od: Peyerimhoff, N, et al.
Izdano: (2023) -
Models for information propagation on graphs
od: Oliver R. A. Dunbar, et al.