Youhuan Li — accepted AI-conference papers

2025

Graph Neural Networks for Databases: A Survey

Ziming Li, Youhuan Li, Yuyu Luo, Guoliang Li, Chuxu Zhang

IJCAI 2025

Graph neural networks (GNNs) are powerful deep learning models for graph-structured data, demonstrating remarkable success across diverse domains. Recently, the database (DB) community has increasingly recognized the potentiality of GNNs, prompting a surge of researches focusing on improving databas

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2023

When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations

Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li +2

ICML 2023poster

Graph Neural Networks (GNNs) are powerful models for non-Euclidean data, but their training is often accentuated by massive unnecessary computation: on the one hand, training on non-Euclidean data has relatively high computational cost due to its irregular density properties; on the other hand, the…

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