Showing 2024Show all
2 papers · 1 filter
cs.LG2024
Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings
Billy Joe Franks, Moshe Eliasof, Semih Cantürk +4
Recent advances in integrating positional and structural encodings (PSEs) into graph neural networks (GNNs) have significantly enhanced their performance across various graph learn…
cs.LG2024
Towards a General Recipe for Combinatorial Optimization with Multi-Filter GNNs
Frederik Wenkel, Semih Cantürk, Stefan Horoi +2
Graph neural networks (GNNs) have achieved great success for a variety of tasks such as node classification, graph classification, and link prediction. However, the use of GNNs (an…