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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Paper Lists for Graph Neural Networks
| Date | Stars |
|---|---|
| 2026-07-31 | 2310 |
| 2026-08-02 | 2310 |
| 2026-08-03 | 2310 |
| 2026-08-06 | 2310 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
## Awesome resources on Graph Neural Networks.
 [](https://awesome.re)  
This is a collection of resources related with graph neural networks.
## Contents
- [Survey papers](#surveypapers)
- [Papers](#papers)
- [Recuurent Graph Neural Networks](#rgnn)
- [Convolutional Graph Neural Networks](#cgnn)
- [Graph Autoencoders](#gae)
- [Network Embedding](#ne)
- [Graph Generation](#gg)
- [Spatial-Temporal Graph Neural Networks](#stgnn)
- [Application](#application)
- [Computer Vision](#cv)
- [Natural Language Processing](#nlp)
- [Internet](#web)
- [Recommender Systems](#rec)
- [Healthcare](#health)
- [Chemistry](#chemistry)
- [Physics](#physics)
- [Others](#others)
- [Library](#library)
<a name="surveypapers" />
## Survey papers
1. **A Comprehensive Survey on Graph Neural Networks.** *Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu.* 2019 [paper](https://arxiv.org/pdf/1901.00596.pdf)
1. **Adversarial Attack and Defense on Graph Data: A Survey.** *Lichao Sun, Yingtong Dou, Carl Yang, Ji Wang, Philip S. Yu, Bo Li.* 2018 [paper](https://arxiv.org/pdf/1812.10528.pdf)
1. **Geometric deep learning: going beyond euclidean data.** *Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst.* 2016. [paper](https://arxiv.org/pdf/1611.08097.pdf)
1. **Relational inductive biases, deep learning, and graph networks.**
*Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gulcehre, Francis Song, Andrew Ballard, Justin Gilmer, George Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu.* 2018. [paper](https://arxiv.org/pdf/1806.01261.pdf)
1. **Attention models in graphs.** *John Boaz Lee, Ryan A. Rossi, Sungchul Kim, Nesreen K. Ahmed, Eunyee Koh.* 2018. [paper](https://arxiv.org/pdf/1807.07984.pdf)
1. **Deep learning on graphs: A survey.** Ziwei Zhang, Peng Cui and Wenwu Zhu. 2018. [paper](https://arxiv.org/pdf/1812.04202.pdf)
1. **Graph Neural Networks: A Review of Methods and Applications** *Jie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Maosong Sun.* 2018 [paper](https://arxiv.org/pdf/1812.08434.pdf)
<a name="papers" />
## Papers
<a name="rgnn" />
## Recurrent Graph Neural Networks
1. **Supervised neural networks for the classification of structures** *A. Sperduti and A. Starita.* IEEE Transactions on Neural Networks 1997. [paper](https://www.ncbi.nlm.nih.gov/pubmed/18255672)
1. **A new model for learning in graph domains.** *Marco Gori, Gabriele Monfardini, Franco Scarselli.* IJCNN 2005. [paper](https://ieeexplore.ieee.org/abstract/document/1555942)
1. **The graph neural network model.** *Franco Scarselli,Marco Gori,Ah Chung Tsoi,Markus Hagenbuchner,
Gabriele Monfardini.* 2009. [paper](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1015.7227&rep=rep1&type=pdf)
1. **Graph echo state networks.** *Claudio Gallicchio, Alessio Micheli* IJCNN 2010. [paper](https://ieeexplore.ieee.org/abstract/document/5596796)
1. **Gated graph sequence neural networks.** *Yujia Li, Richard Zemel, Marc Brockschmidt, Daniel Tarlow.* ICLR 2015. [paper](https://arxiv.org/pdf/1511.05493.pdf)
1. **Learning steady-states of iterative algorithms over graphs.** *Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song* ICML 2018. [paper](http://proceedings.mlr.press/v80/dai18a/dai18a.pdf)
<a name="cgnn" />
## Convolutional Graph Neural Networks
Excerpt of 32,080 characters
Read on GitHub
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2
Guohao Li · CAMEL-AI.org
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Yingtong Dou · Visa Research · United States
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:cbf1d6138ac5da0c, topic:deep-learning