ARO-GNN: Adaptive relation-optimized graph neural networks

Abstract Existing Graph Neural Networks (GNNs) suffer from topological noise and attribute distortion when handling complex topology-attribute interactions. To overcome these limitations, we propose Adaptive Relation-Optimized Graph Neural Networks (ARO-GNN). ARO-GNN utilizes complementary informati...

Full description

Saved in:
Bibliographic Details
Main Authors: Yong Lu, Zhengguo Lin
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Journal of King Saud University: Computer and Information Sciences
Subjects:
Online Access:https://doi.org/10.1007/s44443-025-00198-w
Tags: Add Tag
No Tags, Be the first to tag this record!