Temporal Graph Generative Models

Author:

Souid Houssem Eddine1ORCID,Ody Lucas2ORCID,Achenchabe Youssef3ORCID,Lemaire Valentin2ORCID,Aversano Gianmarco2ORCID,Skhiri Sabri2ORCID

Affiliation:

1. Euranova, Tunis, Tunisia

2. Euranova, Mont-Saint-Guibert, Belgium

3. Euranova, Marseille, France

Publisher

ACM

Reference23 articles.

1. Xiaohui Chen, Yukun Li, Aonan Zhang, and Li-ping Liu. 2022. NVD-iff: Graph Generation through the Diffusion of Node Vectors. arXiv preprint arXiv:2211.10794 (2022).

2. Jase Clarkson, Mihai Cucuringu, Andrew Elliott, and Gesine Reinert. 2022. DAMNETS: A deep autoregressive model for generating Markovian network time series. In Learning on Graphs Conference. PMLR, 23--1.

3. Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, and Dale Schuurmans. 2020. Scalable deep generative modeling for sparse graphs. In International conference on machine learning. PMLR, 2302--2312.

4. Attention-Based Graph Evolution

5. GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation

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