41 citations · 133 across the 8 of their papers we have counts for
6 papers · 1 filter
Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer
Wendong Bi, Xueqi Cheng, Bingbing Xu +3
The data-hungry problem, characterized by insufficiency and low-quality of data, poses obstacles for deep learning models. Transfer learning has been a feasible way to transfer kno…
Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network
Wendong Bi, Bingbing Xu, Xiaoqian Sun +3
Graphs consisting of vocal nodes ("the vocal minority") and silent nodes ("the silent majority"), namely VS-Graph, are ubiquitous in the real world. The vocal nodes tend to have ab…
Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks
Wendong Bi, Bingbing Xu, Xiaoqian Sun +3
Company financial risk is ubiquitous and early risk assessment for listed companies can avoid considerable losses. Traditional methods mainly focus on the financial statements of c…
Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) are popular machine learning methods for modeling graph data. A lot of GNNs perform well on homophily graphs while having unsatisfactory performance on…
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) have shown expressive performance on graph representation learning by aggregating information from neighbors. Recently, some studies have discussed the…
Towards Better Understanding of Disentangled Representations via Mutual Information
Xiaojiang Yang, Wendong Bi, Yitong Sun +2
Most existing works on disentangled representation learning are solely built upon an marginal independence assumption: all factors in disentangled representations should be statist…