The following publications are possibly variants of this publication:
- DGA-GNN: Dynamic Grouping Aggregation GNN for Fraud DetectionMingjiang Duan, Tongya Zheng, Yang Gao, Gang Wang, Zunlei Feng, Xinyu Wang. AAAI 2024: 11820-11828 [doi]
- ApeGNN: Node-Wise Adaptive Aggregation in GNNs for RecommendationDan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, Jie Tang 0001. WWW 2023: 759-769 [doi]
- ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware SamplingZhen Song, Yu Gu 0002, Tianyi Li 0005, Qing Sun, Yanfeng Zhang, Christian S. Jensen, Ge Yu 0001. pacmmod, 1(4), December 2023. [doi]
- When Do GNNs Work: Understanding and Improving Neighborhood AggregationYiqing Xie, Sha Li, Carl Yang, Raymond Chi-Wing Wong, Jiawei Han 0001. IJCAI 2020: 1303-1309 [doi]
- RAW-GNN: RAndom Walk Aggregation based Graph Neural NetworkDi Jin, Rui Wang, Meng Ge, Dongxiao He, Xiang Li, Wei Lin, Weixiong Zhang. IJCAI 2022: 2108-2114 [doi]