# TrustAGI-Lab/ARGA

<https://repo.masters-masters.com/en/repos/TrustAGI-Lab/ARGA>

[Home](https://repo.masters-masters.com/en) › [TrustAGI-Lab](https://repo.masters-masters.com/en/owners/TrustAGI-Lab) › [ARGA](https://repo.masters-masters.com/en/repos/TrustAGI-Lab/ARGA)

TrustAGI-Lab/ARGA has 185 stars on GitHub. Its RepoMasters card: Prototype tier. This is a TensorFlow implementation of the Adversarially Regularized Graph…

| Field | Value |
| --- | --- |
| Owner | [TrustAGI-Lab](https://repo.masters-masters.com/en/owners/TrustAGI-Lab) |
| Stars | 185 |
| Forks | 58 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2018 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [TrustAGI-Lab/ARGA](https://github.com/TrustAGI-Lab/ARGA) |

## Repository

This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., & Zhang, C. (2018). Adversarially Regularized Graph Autoencoder for Graph Embedding, \[https://www.ijcai.org/proceedings/2018/0…

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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