Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.


Half a decade of graph convolutional networks

Graph convolutional networks have become a popular tool for learning with graphs and networks. We reflect on the reasons behind the success story.

This is a preview of subscription content

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Scheme for a graph neural network.


  1. Kipf, T. N. & Welling, M. in International Conference on Learning Representations (2017).

  2. Hamilton, W. L., Ying, Z. & Leskovec, J. in Advances in Neural Information Processing Systems 30 (NIPS 2017) 1024–1034 (Conference on Neural Information Processing Systems, 2017).

  3. Velickovic, P., Cucurull, G., Casanova, A., Romero, A., Liò, P. & Bengio, Y. in International Conference on Learning Representations (2018).

  4. Xu, K., Hu, W., Leskovec, J. & Jegelka S. in International Conference on Learning Representations (2019).

  5. Zhang, M. & Chen, Y. in Advances in Neural Information Processing Systems 30 (NIPS 2018) 5171–5181 (Conference on Neural Information Processing Systems, 2018).

  6. Wang, D., Liu, P., Zheng, Y., Qiu, X. & Huang, X. in Association for Computational Linguistics (ACL) 6209–6219 (2020).

  7. Xu, J., Zhu, Z., Zhao, J., Liu, X., Shan, M. & Guo, J. in ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD), 3356–3365 (Association for Computing Machinery, 2020).

  8. Emmert-Streib, F., Yli-Harja, O. & Dehmer, M. WIREs Data Mining and Knowledge Discovery 10, e1368 (2020).

    Article  Google Scholar 

  9. Arrieta, A. B. et al. Inf. Fusion 58, 82–115 (2020).

    Article  Google Scholar 

  10. Wu, F., Souza, A. H. Jr, Zhang, T., Fifty, C., Yu, T. & Weinberger, K. Q. in Proc. of the 36th International Conference on Machine Learning (ICML) 6861–6871 (2019).

  11. Dou, Y., Shu, K., Xia, C., Yu, P. S. & Sun, L. in SIGIR '21: Proc. of the 44th International ACM SIGIR Conference on Research and Development in Information 2051–2055 (Association for Computing Machinery, 2021).

  12. Liu, Y., Wang, W., Hu, Y., Hao, J., Chen, X. & Gao, Y. in Proc. of the AAAI Conference on Artificial Intelligence 34, 7211–7218 (Association for the Advancement of Artificial Intelligence, 2020).

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Mostafa Haghir Chehreghani.

Ethics declarations

Competing interest

The author declares no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Haghir Chehreghani, M. Half a decade of graph convolutional networks. Nat Mach Intell 4, 192–193 (2022).

Download citation

  • Published:

  • Issue Date:

  • DOI:


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing