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CondGen

Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.

Install / Use

/learn @KelestZ/CondGen
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Implementation of CondGen, NeurIPS 2019.

Please cite the following work if you find the code useful.

@inproceedings{yang2018meta,
	Author = {Yang, Carl and Zhuang, Peiye and Shi, Wenhan and Luu, Alan and Pan, Li},
	Booktitle = {NeurIPS},
	Title = {Conditional structure generation through graph variational generative adversarial nets},
	Year = {2019}
}

Contact: Peiye Zhuang (peiye@illinois.edu), Carl Yang (yangji9181@gmail.com)

Results

Prerequisites

  • Python3
  • Pytorch 0.4
  • Tookits like python-igraph, powerlaw, networkx etc.

Data

Our DBLP dataset and TCGA dataset are released on Google Drive.

Training

python train.py

with default setttings in options.py.

View on GitHub
GitHub Stars53
CategoryEducation
Updated3mo ago
Forks11

Languages

Python

Security Score

82/100

Audited on Dec 9, 2025

No findings