120 citations · 150 across the 10 of their papers we have counts for
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cs.LG2023
Federated Learning over Coupled Graphs
Runze Lei, Pinghui Wang, Junzhou Zhao +6
Graphs are widely used to represent the relations among entities. When one owns the complete data, an entire graph can be easily built, therefore performing analysis on the graph i…
cs.LG2020★ 23 cited
Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding
Lin Lan, Pinghui Wang, Xuefeng Du +3
We study the problem of node classification on graphs with few-shot novel labels, which has two distinctive properties: (1) There are novel labels to emerge in the graph; (2) The n…
cs.LG2019★ 120 cited
MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
Nuo Xu, Pinghui Wang, Long Chen +2
Predicting interactions between structured entities lies at the core of numerous tasks such as drug regimen and new material design. In recent years, graph neural networks have bec…