787 citations · 2.9k across the 66 of their papers we have counts for
4 papers · 1 filter
CogDL: A Comprehensive Library for Graph Deep Learning
Yukuo Cen, Zhenyu Hou, Yan Wang +15
Graph neural networks (GNNs) have attracted tremendous attention from the graph learning community in recent years. It has been widely adopted in various real-world applications fr…
A Multi-Semantic Metapath Model for Large Scale Heterogeneous Network Representation Learning
Xuandong Zhao, Jinbao Xue, Jin Yu +2
Network Embedding has been widely studied to model and manage data in a variety of real-world applications. However, most existing works focus on networks with single-typed nodes o…
Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
Ninghao Liu, Qiaoyu Tan, Yuening Li +3
Networks have been widely used as the data structure for abstracting real-world systems as well as organizing the relations among entities. Network embedding models are powerful to…
Representation Learning for Attributed Multiplex Heterogeneous Network
Yukuo Cen, Xu Zou, Jianwei Zhang +3
Network embedding (or graph embedding) has been widely used in many real-world applications. However, existing methods mainly focus on networks with single-typed nodes/edges and ca…