[论文精读]Inductive Representation Learning on Large Graphs

论文原文：Inductive representation learning on large graphs | Proceedings of the 31st International Conference on Neural Information Processing Systems (acm.org)

英文是纯手打的！论文原文的summarizing and paraphrasing。可能会出现难以避免的拼写错误和语法错误，若有发现欢迎评论指正！文章偏向于笔记，谨慎食用！

1. 省流版

1.1. 心得

1.2. 论文框架图

2. 论文逐段精读

2.1. Abstract

①The previous works do not concern unseen nodes, only focus on nodes which are presented or labeled

②They adopt inductive framework by sampling and aggregating features from neighbors

2.2. Introduction

2.3. Related work

2.4. Proposed method: GraphSAGE

2.4.1. Embedding generation (i.e., forward propagation) algorithm

2.4.2. Learning the parameters of GraphSAGE

2.4.3. Aggregator Architectures

2.5. Experiments

2.5.1. Inductive learning on evolving graphs: Citation and Reddit data

2.5.2. Generalizing across graphs: Protein-protein interactions

2.5.3. Runtime and parameter sensitivity

2.5.4. Summary comparison between the different aggregator architectures

2.6. Theoretical analysis

2.7. Conclusion

3. 知识补充

4. Reference List