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Found 4 papers, 2 papers with code
Interpreting and Unifying Graph Neural Networks with An Optimization Framework
Graph Neural Networks (GNNs) have received considerable attention on graph-structured data learning for a wide variety of tasks.
Heterogeneous Graph Neural Network for Recommendation
The prosperous development of e-commerce has spawned diverse recommendation systems.
Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification
Then, we propose Heterogeneous Graph ATtention networks (HGAT) to embed the HIN for short text classification based on a dual-level attention mechanism, including node-level and type-level attentions.
Heterogeneous Graph Attention Network
With the learned importance from both node-level and semantic-level attention, the importance of node and meta-path can be fully considered.
Ranked #1 on
Heterogeneous Node Classification
on DBLP (PACT) 14k
Social and Information Networks
