【KDD 2019】Heterogeneous Graph Neural Network
背景 Representation learning in heterogeneous graphs aims to pursue a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized rec
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相關文章
- 1. 論文筆記：KDD 2019 Heterogeneous Graph Neural Network
- 2. 【論文解讀 KDD 2019 | HetGNN】Heterogeneous Graph Neural Network
- 3. 【論文解讀 KDD 2019 | MEIRec】Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation
- 4. KDD19開源論文 Heterogeneous Graph Neural Network
- 5. Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation
- 6. 論文筆記：WWW 2019 Heterogeneous Graph Attention Network
- 7. 【KDD 2020】 HGCN: A Heterogeneous Graph Convolutional Network-Based Deep Learning Model Toward Collec
- 8. Graph Neural Network Review
- 9. 《Heterogeneous Graph Attention Network》論文解讀
- 10. 【論文解讀 KDD 2019 | GATNE 】Representation Learning for Attributed Multiplex Heterogeneous Network