Fusing multiplex heterogeneous networks using graph attention-aware fusion networks

Abstract Graph Neural Networks (GNN) emerged as a deep learning framework to generate node and graph embeddings for downstream machine learning tasks. Popular GNN-based architectures operate on networks of single node and edge type. However, a large number of real-world networks include multiple typ...

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Bibliographic Details
Main Authors: Ziynet Nesibe Kesimoglu, Serdar Bozdag
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-024-78555-4
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