Graph-Neural-Networks.md

@@ -78,7 +78,12 @@ Commonly the below terms are referred to the same thing.
 1. **Self-Supervised Learning of Graph Neural Networks: A unified view.** TPAMI 2022. [paper](https://ieeexplore.ieee.org/abstract/document/9764632)
 
     *Yaochen Xie, Zhao Xu, Jingtun Zhang, Zhangyang Wang, Shuiwang Ji.*
-### Technical Papers
+### Popular Models
+GCN, GraphSage, GAT
+-[GCN]**Semi-supervised classification with graph convolutional networks.** *Thomas N. Kipf, Max Welling.* ICLR 2017. [paper](https://arxiv.org/pdf/1609.02907.pdf)
+-[GraphSage] **Inductive representation learning on large graphs.** *William L. Hamilton, Rex Ying, Jure Leskovec.* NIPS 2017. [paper](http://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf)
+-[GAT] **Graph Attention Networks.** *Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio.* ICLR 2018. [paper](https://arxiv.org/pdf/1710.10903.pdf) [code](
+- [SGC] **Simplifying Graph Convolutional Networks.** *Felix Wu, Tianyi Zhang, Amauri Holanda de Souza Jr., Christopher Fifty, Tao Yu, Kilian Q. Weinberger.* ICML 2019. [paper](https://arxiv.org/pdf/1902.07153.pdf) [code](https://github.com/Tiiiger/SGC)
 ### Evaluation Papers 
 
 ## Awesome Resource Collections