24 citations · 28 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
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.…
Domain-adversarial Network Alignment
Huiting Hong, Xin Li, Yuangang Pan +1
Network alignment is a critical task to a wide variety of fields. Many existing works leverage on representation learning to accomplish this task without eliminating domain represe…
GANE: A Generative Adversarial Network Embedding
Huiting Hong, Xin Li, Mingzhong Wang
Network embedding has become a hot research topic recently which can provide low-dimensional feature representations for many machine learning applications. Current work focuses on…