GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS
Introduction 提出了一种新的基于注意力的图序列学习神经网络模型Graph2Seq。Graph2Seq模型遵循传统的编解码器方法，包含两个主要组件，一个图形编码器和一个序列解码器。本文提出的图形编码器旨在学习表达性节点嵌入，并将其重新组合成相应的图形嵌入。为此,灵感来自最近的图表示学习方法(汉密尔顿et al ., 2017),我们建议归纳基于神经网络学习节点从节点属性通过聚合社区信息嵌
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相关文章
- 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. 【论文阅读】Sequence to Sequence Learning with Neural Network
- 8. 《Sequence to Sequence Learning with Neural Networks》阅读笔记
- 9. Sequence to Sequence Learning with Neural Networks学习笔记
- 10. 【论文阅读】Sequence to Sequence Learning with Neural Networks