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Found 4 papers, 2 papers with code
Meta Graph Attention on Heterogeneous Graph with Node-Edge Co-evolution
Graph neural networks have become an important tool for modeling structured data.
An Attention-based Graph Neural Network for Heterogeneous Structural Learning
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
Network alignment is a critical task to a wide variety of fields.
GANE: A Generative Adversarial Network Embedding
Network embedding has become a hot research topic recently which can provide low-dimensional feature representations for many machine learning applications.
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