Graph network classification（As a beginner, continue to update）

Data arrangement

1.Reference Webs

http://nlp.csai.tsinghua.edu.cn/~tcc/

https://blog.youkuaiyun.com/a609640147/article/details/89562262

https://blog.youkuaiyun.com/liudingbobo/article/details/83039233

https://blog.youkuaiyun.com/lzglzj20100700/article/details/84965339

https://blog.youkuaiyun.com/weixin_39373480/article/details/89402879

https://blog.youkuaiyun.com/r1254/article/details/88343349

https://blog.youkuaiyun.com/qq_41727666/article/details/84587027

https://blog.youkuaiyun.com/weixin_42137700/article/details/87159371

https://blog.youkuaiyun.com/melon0014/article/details/82527750

https://blog.youkuaiyun.com/u014281392/article/details/90174664

https://blog.youkuaiyun.com/DSTJWJW/article/details/83896312

https://blog.youkuaiyun.com/qq_34911465/article/details/88524599

http://i.dataguru.cn/mportal.php?mod=view&aid=14801

https://mp.weixin.qq.com/s?src=11&timestamp=1561431089&ver=1689&signature=EMOEnQ2reNbnmTwed8JVBNlMfbPiT3kg79ZslP0gMBNTyn20BQIsAL-vW8FG3aPfjhAr2eZ8G*WYkOdonzgEixDKstBpumlm8wKbCbWtd7RKgrSBkmWLVxfJ5FJeDfNx&new=1

2.Reference Papers

https://www.cs.purdue.edu/mlg2011/papers/paper_1.pdf

https://link.springer.com/content/pdf/10.1007%2F978-1-4419-6045-0.pdf

https://link.springer.com/content/pdf/10.1007%2F978-1-4419-6045-0.pdf

https://www.cse.wustl.edu/~muhan/papers/AAAI_2018_DGCNN.pdf

http://ryanrossi.com/pubs/KDD18-graph-attention-model.pdf

https://www.cs.uoregon.edu/Reports/AREA-201706-Riazi.pdf

https://paperswithcode.com/task/graph-classification

https://www.kdd.org/kdd2018/accepted-papers/view/graph-classification-using-structural-attention

https://www.csc2.ncsu.edu/faculty/nfsamato/practical-graph-mining-with-R/slides/pdf/Classification.pdf

3.Others

Semi-Supervised Classification with Graph Convolutional Networks

Graph Partition Neural Networks for Semi-Supervised Classification

FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

Generating Classification Weights With GNN Denoising Autoencoders for Few-Shot Learning

Link Prediction Based on Graph Neural Networks

Hierarchical Graph Representation Learning with Differentiable Pooling

还可以到CVPR，ICLR，NIPS，这几个会议上去找找（待找）

转载于:https://www.cnblogs.com/Ann21/p/11083402.html