… a novel semi-supervised graph neural network for heterogeneous graph. Our model follows
a hierarchical attention structure: node-level attention → semantic-level attention. Figure 2 …

… Our model aims to learn a unified subspace common for all domains with a heterogeneous
graph attention network, where the transductive ability of the graph attention network can …

… HIN (heterogeneous information network) framework for … Heterogeneous Graph ATtention
networks (HGAT) to embed the HIN for short text classification based on a dual-level attention …

… However, existing heterogeneous graph neural networks … entangled heterogeneous graph
attention network DisenHAN … aspects in a heterogeneous information network. In particular, …

… , there is no research method specifically for heterogeneous networks. … graph attention
network (HDGAN), which attempts to use the attention mechanism to take the heterogeneity and …

… In this work, we design a heterogeneous edge-featured graph attention network (HEAT), an
extension of GAT, for the proposed comprehensive interaction representation. HEAT can be …

… a flexible heterogeneous information network (HIN) … Heterogeneous Graph Attention
networks (HGAT) to embed the HIN for short text classification based on a dual-level attention …

… heterogeneous graph attention networks, called HetNet, to learn efficient and diverse
communication models for coordinating heterogeneous … We propose a Multi-Agent …

… by heterogeneous graph attention network (HGAT) [31], we develop a novel heterogeneous
graph attention network … , and then construct a heterogeneous graph by incorporating the …

… -supervised classification task in the heterogeneous graph, opening up an opportunity of …
heterogeneous graph attention networks framework HGAT, sufficiently leveraging the graph …