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 |
---|---|
פורמט: | Conference item |
שפה: | English |
יצא לאור: |
Journal of Machine Learning Research
2022
|
פריטים דומים
-
Expanders, rank and graphs of groups
מאת: Lackenby, M
יצא לאור: (2004) -
How does over-squashing affect the power of GNNs?
מאת: Di Giovanni, F, et al.
יצא לאור: (2024) -
Expander graphs
מאת: Kahale, Nabil
יצא לאור: (2005) -
Parameterized counting and Cayley graph expanders
מאת: Peyerimhoff, N, et al.
יצא לאור: (2023) -
Models for information propagation on graphs
מאת: Oliver R. A. Dunbar, et al.