3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2026
PreGS: A Parameter-Transfer-Based Multi-Expert Graph Neural Network for Node Classification
Zhicong Cai, Yinglong Zhang, Xiaoying Hong +2
Graph neural networks have achieved strong performance in node classification by aggregating information from graph neighborhoods. However, a single aggregation mechanism may be in…
cs.LG2024★ 3 cited
TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation Learning
Jiawei E, Yinglong Zhang, Xuewen Xia +1
In the field of deep learning, Graph Neural Networks (GNNs) and Graph Transformer models, with their outstanding performance and flexible architectural designs, have become leading…