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cs.LG2023
A Local Graph Limits Perspective on Sampling-Based GNNs
Yeganeh Alimohammadi, Luana Ruiz, Amin Saberi
We propose a theoretical framework for training Graph Neural Networks (GNNs) on large input graphs via training on small, fixed-size sampled subgraphs. This framework is applicable…
cs.LG2023
Locality-Aware Graph-Rewiring in GNNs
Federico Barbero, Ameya Velingker, Amin Saberi +2
Graph Neural Networks (GNNs) are popular models for machine learning on graphs that typically follow the message-passing paradigm, whereby the feature of a node is updated recursiv…