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Feature transportation improves graph neural networks
Paper Details
Published: 2024/03/24
Volume: 38
Number: 11
Pages: 11874-11882
DOI: 10.1609/aaai.v38i11.29073
Container Title: AAAI Conference on Artificial Intelligence
Paper Links
WebsiteGraph neural networks (GNNs) have shown remarkable success in learning representations for graph-structured data. However, GNNs still face challenges in modeling complex phenomena that involve feature transportation. In this paper, the authors propose a novel GNN architecture inspired by Advection-Diffusion-Reaction systems, called ADR-GNN and show that it improves or offers competitive performance compared to state-of-the-art networks.
