| 名称 | 来源 | 说明 | 状态 | 备注 |
|---|---|---|---|---|
| 《Tackling Graphical NLP problems with Graph Recurrent Networks》 | Arxiv2019 | 图网络在NLP中的应用； Linfeng Song 博士论文 |
NULL | NULL |
| 《阿尔伯塔大学博士毕业论文：基于图结构的自然语言处理》 | NULL | Bang Liu 博士论文 | NULL | https://mp.weixin.qq.com/s/BXovM5bHshLxdmBg93EQrA https://sites.ualberta.ca/~bang3/files/PhD-Thesis.pdf https://sites.ualberta.ca/~bang3/publication.html |
| 《Convolutional Networks on Graphs for Learning Molecular Fingerprints》 | NIPS2015 | 经典空域GCN（Neural FPs | NULL | NULL |
| 《SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS》 | ICLR2017 | 经典频域GCN | NULL | NULL |
| 《The graph neural network model》 | IEEE Transactions on Neural Networks 2009 | 经典GNN | NULL | NULL |
| 《Deepwalk: Online learning of social representations》 | SIGKDD 2014 | DeepWalk is regarded as the first graph embedding method based on representation learning, applies | ||
| SkipGram model on the generated random walks. | NULL | NULL | ||
| 《HOW POWERFUL ARE GRAPH NEURAL NETWORKS?》 | ICLR2019 | GIN（哔哩哔哩上有视频讲解） | NULL | NULL |
| 《Learning Convolutional Neural Networks for Graphs》 | ICML2016 | 经典空域GCN（PATCHY-SAN，有官方PPT讲解） | NULL | NULL |
| 《Graph Neural Networks:A Review of Methods and Applications》 | Arxiv2019 | GNN综述（清华孙茂松） | NULL | NULL |
| 《A Comprehensive Survey on Graph Neural Networks》 | Arxiv2019 | GNN综述（IEEE fellow Zonghan Wu） | NULL | NULL |
| 《Deep Learning on Graphs: A Survey》 | Arxiv2019 | GNN综述（清华朱文武） | NULL | NULL |
| 《LINE: Large-scale Information Network Embedding》 | WWW2015 | 图嵌入（公司推荐特征推荐使用） | NULL | NULL |
| 《Graph Attention Networks》 | ICLR2018 | GAT | NULL | NULL |
| 《struc2vec: Learning Node Representations from Structural Identity》 | NULL | NULL | NULL | NULL |
| 《GraphSAINT: Graph Sampling Based Inductive Learning Method》 | ICLR2020 | NULL | NULL | NULL |
| 《GraphSage: Graph Sampling Based Inductive Learning Method》 | NIPS2017 | NULL | NULL | NULL |
| DROPEDGE: TOWARDS DEEP GRAPH CONVOLUTIONAL NETWORKS ON NODE CLASSIFICATION》 | NULL | NULL | NULL | NULL |
| NULL | NULL | NULL | NULL | NULL |
| NULL | NULL | NULL | NULL | NULL |
| NULL | NULL | NULL | NULL | NULL |
| NULL | NULL | NULL | NULL | NULL |