GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS
Introduction 提出了一種新的基於注意力的圖序列學習神經網絡模型Graph2Seq。Graph2Seq模型遵循傳統的編解碼器方法，包含兩個主要組件，一個圖形編碼器和一個序列解碼器。本文提出的圖形編碼器旨在學習表達性節點嵌入，並將其重新組合成相應的圖形嵌入。爲此,靈感來自最近的圖表示學習方法(漢密爾頓et al ., 2017),我們建議歸納基於神經網絡學習節點從節點屬性通過聚合社區信息嵌
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相關文章
- 1. Sutskever2014_Sequence to Sequence Learning with Neural Networks
- 2. Paper：Sequence to Sequence Learning with Neural Networks
- 3. (25)[NIPS14] Sequence to Sequence Learning with Neural Networks
- 4. Few-Shot Learning with Graph Neural Networks
- 5. Few-shot Learning with Graph Neural Networks
- 6. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORK
- 7. 【論文閱讀】Sequence to Sequence Learning with Neural Network
- 8. 《Sequence to Sequence Learning with Neural Networks》閱讀筆記
- 9. Sequence to Sequence Learning with Neural Networks學習筆記
- 10. 【論文閱讀】Sequence to Sequence Learning with Neural Networks