Inductive Matrix Completion Based on Graph Neural Networks
參考文獻 Inductive Matrix Completion Based on Graph Neural Networks - ICLR 2020 〇、相關工作 1、Graph Neural Network 圖神經網絡(GNNs)是一種用於在圖形上學習的新型神經網絡。主要分爲兩種類型：Node Level GNNs和Graph Level GNNs。Nodelevel GNNs使用消息傳遞層在
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相關文章
- 1. Graph Convolutional Matrix Completion
- 2. Paper Notes: A Comprehensive Survey on Graph Neural Networks
- 3. Graph-based Dependency Parsing with Graph Neural Networks
- 4. 論文筆記：Graph Convolutional Matrix Completion
- 5. GraphSAINT: Graph Sampling Based Inductive Learning Method
- 6. CS224W-08-Graph Neural Networks
- 7. GNN:Session-based Recommendation with Graph Neural Networks簡介
- 8. GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS
- 9. Applications of Graph Neural Networks
- 10. 【論文筆記】Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks