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GraphGAN

A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)

Model DevelopmentArchitecturePython
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创建于 2017-11-19 · 更新于 2026-10-13 · 今日第 17460 名
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hwwang55wangjialin114suanrong

hwwang55/GraphGAN 排名第 17,460，有 538 个星标。

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hwwang55/GraphGAN 排名第 17,460，此处有 8 个同类条目；mlfoundations/open_lm 排名第 17,463。

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关键参数与规格
关键参数与规格
参数值
语言Python
类别Model Development
子类别Architecture
关键词Graph neural networks
星标数538
分叉数156
贡献者3
创建日期2017-11-19
更新日期2026-10-13
1 天星标数0
7 天星标数1
排名17,460
上次排名17,246
排名变化-214
7 天星标排名11,439
上次 7 天星标排名11,498
7 天星标排名变化59
总星标排名18,282
上次总星标排名18,255
总星标排名变化-27
国家USA
README 摘录

GraphGAN This repository is the implementation of GraphGAN (arXiv): GraphGAN: Graph Representation Learning With Generative Adversarial Nets Hongwei Wang, Jia Wang, Jialin Wang, Miao Zhao, Weinan Zhang, Fuzheng Zhang, Xing Xie, Minyi Guo 32nd AAAI Conference on Artificial Intelligence, 2018 GraphGAN unifies two schools of graph representation learning methodologies: generative methods and discriminative methods, via adversarial training in a minimax game. The generator is guided by the signals from the discriminator and improves its generating performance, while the discriminator is

pushed by the generator to better distinguish ground truth from generated samples. Files in the folder : training and test data : pre-trained node embeddings Note: the dimension of pre-trained node embeddings should equal n_emb in src/GraphGAN/config. py : evaluation results and the learned embeddings of the generator and the discriminator : source codes Requirements The code has been tested running under Python 3. 5, with the following packages installed (along with their dependencies): tensorflow == 1. 4 (for displaying

the progress bar) numpy == 1. 1 Input format The input data should be an undirected graph in which node IDs start from *0* to *N-1* (*N* is the number of nodes in the graph). Each line contains two node IDs indicating an edge in the graph.

常见问题

记录了多少星标和分叉？

hwwang55/GraphGAN 有 538 个星标和 156 个分叉。

仓库排名是多少？

hwwang55/GraphGAN 排名第 17,460。

记录的语言和类别是什么？

hwwang55/GraphGAN 有 538 个星标，语言为 Python，类别为 Model Development。

哪个仓库排名最接近？

hwwang55/GraphGAN 与 mlfoundations/open_lm 比较，后者排名第 17,463，有 538 个星标。

README

GraphGAN

GraphGAN: Graph Representation Learning With Generative Adversarial Nets
Hongwei Wang, Jia Wang, Jialin Wang, Miao Zhao, Weinan Zhang, Fuzheng Zhang, Xing Xie, Minyi Guo
32nd AAAI Conference on Artificial Intelligence, 2018

GraphGAN unifies two schools of graph representation learning methodologies: generative methods and discriminative methods, via adversarial training in a minimax game. The generator is guided by the signals from the discriminator and improves its generating performance, while the discriminator is pushed by the generator to better distinguish ground truth from generated samples.

Files in the folder

  • data/: training and test data
  • pre_train/: pre-trained node embeddings

    Note: the dimension of pre-trained node embeddings should equal n_emb in src/GraphGAN/config.py

  • results/: evaluation results and the learned embeddings of the generator and the discriminator
  • src/: source codes

Requirements

The code has been tested running under Python 3.6.5, with the following packages installed (along with their dependencies):

  • tensorflow == 1.8.0
  • tqdm == 4.23.4 (for displaying the progress bar)
  • numpy == 1.14.3
  • sklearn == 0.19.1

Input format

The input data should be an undirected graph in which node IDs start from 0 to N-1 (N is the number of nodes in the graph). Each line contains two node IDs indicating an edge in the graph.

txt file sample

0 1
3 2
...

Basic usage

mkdir cache
cd src/GraphGAN
python graph_gan.py

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