3 papers
cs.LG2026
Learning Structure-Semantic Evolution Trajectories for Graph Domain Adaptation
Wei Chen, Xingyu Guo, Shuang Li +7
Graph Domain Adaptation (GDA) aims to bridge distribution shifts between domains by transferring knowledge from well-labeled source graphs to given unlabeled target graphs. One pro…
cs.LG2025
Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation
Wei Chen, Guo Ye, Yakun Wang +5
Unsupervised Graph Domain Adaptation (UGDA) seeks to bridge distribution shifts between domains by transferring knowledge from labeled source graphs to given unlabeled target graph…
cs.LG2023
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction
Yakun Wang, Binbin Hu, Shuo Yang +6
The rapid development of graph neural networks (GNNs) encourages the rising of link prediction, achieving promising performance with various applications. Unfortunately, through a…