Graph network classification（As a beginner, continue to update）
Data arrangement
1.Reference Webs
http://nlp.csai.tsinghua.edu.cn/~tcc/
https://blog.csdn.net/a609640147/article/details/89562262
https://blog.csdn.net/liudingbobo/article/details/83039233
https://blog.csdn.net/lzglzj20100700/article/details/84965339
https://blog.csdn.net/weixin_39373480/article/details/89402879
https://blog.csdn.net/r1254/article/details/88343349
https://blog.csdn.net/qq_41727666/article/details/84587027
https://blog.csdn.net/weixin_42137700/article/details/87159371
https://blog.csdn.net/melon0014/article/details/82527750
https://blog.csdn.net/u014281392/article/details/90174664
https://blog.csdn.net/DSTJWJW/article/details/83896312
https://blog.csdn.net/qq_34911465/article/details/88524599
http://i.dataguru.cn/mportal.php?mod=view&aid=14801
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
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）
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