BOOK-CHAPTER

Revisiting Attention-Based Graph Neural Networks for Graph Classification

Ye TaoYing LiZhonghai Wu

Year: 2022 Lecture notes in computer science Pages: 442-458   Publisher: Springer Science+Business Media
Keywords:
Computer science Graph Expressive power Theoretical computer science Benchmark (surveying) Node (physics) Artificial intelligence

Metrics

2
Cited By
0.73
FWCI (Field Weighted Citation Impact)
27
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Graph Neural Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Ferroelectric and Negative Capacitance Devices
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

Related Documents

JOURNAL ARTICLE

Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification

Xin WangHeng ChangBeini XieTian BianShiji ZhouDaixin WangZhiqiang ZhangWenwu Zhu

Journal:   IEEE Transactions on Knowledge and Data Engineering Year: 2023 Vol: 36 (5)Pages: 2166-2178
JOURNAL ARTICLE

Global Attention-Based Graph Neural Networks for Node Classification

Jiusheng ChenChengyuan FangXiaoyu Zhang

Journal:   Neural Processing Letters Year: 2022 Vol: 55 (4)Pages: 4127-4150
© 2026 ScienceGate Book Chapters — All rights reserved.