“GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models”

By Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec. 2018

Subfields: Generative Models, Graph Learning

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Generative Models

1. Emiel Hoogeboom
2. Victor Garcia Satorras
3. Max Welling
4. Stefano Ermon
5. Yoshua Bengio
6. Fei Ye
7. Adrian G. Bors
8. Diederik P. Kingma

In Graph Learning

1. Max Welling
2. Victor Garcia Satorras
3. Emiel Hoogeboom
4. Jure Leskovec
5. William L. Hamilton
6. Jian Tang
7. Stephan Günnemann
8. Rex Ying

Citations in the corpus

• E(n) Equivariant Graph Neural Networks (2021, methodology): “• Community Small: We used the original code from (You et al., 2018) (https://github.com/JiaxuanYou/graph-generation) to generate a Community Small dataset.”