Determining the optimal number of GAT and GCN layers for node classification in graph neural networks

Node classification in complex networks plays an important role including social network analysis and recommendation systems. Some graph neural networks such as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) have emerged as effective approaches for achieving high-performance c...

Full description

Bibliographic Details

Main Authors:	Noor, Humaira, Islam, Niful, Hossain Mukta, Md Saddam, Nur Shazwani, Kamarudin, Khan Raiaan, Mohaimenul Azam, Azam, Sami
Format:	Conference or Workshop Item
Language:	en en
Published:	Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/40357/1/Determining%20the%20optimal%20number%20of%20GAT%20and%20GCN.pdf http://umpir.ump.edu.my/id/eprint/40357/2/Determining%20the%20optimal%20number%20of%20GAT%20and%20GCN%20layers%20for%20node%20classification%20in%20graph%20neural%20networks_ABS.pdf http://umpir.ump.edu.my/id/eprint/40357/ https://doi.org/10.1109/ICSECS58457.2023.10256323
Tags:	Add Tag No Tags, Be the first to tag this record!