24 citations · 29 across the 5 of their papers we have counts for
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cs.LG2020
Meta Graph Attention on Heterogeneous Graph with Node-Edge Co-evolution
Yucheng Lin, Huiting Hong, Xiaoqing Yang +3
Graph neural networks have become an important tool for modeling structured data. In many real-world systems, intricate hidden information may exist, e.g., heterogeneity in nodes/e…
cs.LG2019★ 24 cited
An Attention-based Graph Neural Network for Heterogeneous Structural Learning
Huiting Hong, Hantao Guo, Yucheng Lin +3
In this paper, we focus on graph representation learning of heterogeneous information network (HIN), in which various types of vertices are connected by various types of relations.…