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https://github.com/nicola-decao/MolGAN
Tensorflow implementation of MolGAN: An implicit generative model for small molecular graphs
https://github.com/nicola-decao/MolGAN
Last synced: about 1 month ago
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Tensorflow implementation of MolGAN: An implicit generative model for small molecular graphs
- Host: GitHub
- URL: https://github.com/nicola-decao/MolGAN
- Owner: nicola-decao
- License: mit
- Created: 2018-09-24T10:54:43.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2023-10-25T15:08:32.000Z (about 1 year ago)
- Last Synced: 2024-08-01T17:25:09.722Z (4 months ago)
- Language: Python
- Homepage: https://arxiv.org/abs/1805.11973
- Size: 32.2 KB
- Stars: 252
- Watchers: 8
- Forks: 85
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-graph-classification - [Python Reference
README
# MolGAN
Tensorflow implementation of MolGAN: An implicit generative model for small molecular graphs (https://arxiv.org/abs/1805.11973)## Overview
This library contains a Tensorflow implementation of MolGAN: An implicit generative model for small molecular graphs as presented in [[1]](#citation)(https://arxiv.org/abs/1805.11973).
## Dependencies* **python>=3.6**
* **tensorflow>=1.7.0**: https://tensorflow.org
* **rdkit**: https://www.rdkit.org
* **numpy**
* **scikit-learn**## Structure
* [data](https://github.com/nicola-decao/MolGAN/tree/master/data): should contain your datasets. If you run `download_dataset.sh` the script will download the dataset used for the paper (then you should run `utils/sparse_molecular_dataset.py` to convert the dataset in a graph format used by MolGAN models).
* [example](https://github.com/nicola-decao/MolGAN/blob/master/example.py): Example code for using the library within a Tensorflow project. **NOTE: these are NOT the experiments on the paper!**
* [models](https://github.com/nicola-decao/MolGAN/tree/master/models): Class for Models. Both VAE and (W)GAN are implemented.
* [optimizers](https://github.com/nicola-decao/MolGAN/tree/master/optimizers): Class for Optimizers for both VAE, (W)GAN and RL.## Usage
Please have a look at the [example](https://github.com/nicola-decao/MolGAN/blob/master/example.py).Please cite [[1](#citation)] in your work when using this library in your experiments.
## Feedback
For questions and comments, feel free to contact [Nicola De Cao](mailto:[email protected]).## License
MIT## Citation
```
[1] De Cao, N., and Kipf, T. (2018).MolGAN: An implicit generative
model for small molecular graphs. ICML 2018 workshop on Theoretical
Foundations and Applications of Deep Generative Models.
```BibTeX format:
```
@article{de2018molgan,
title={{MolGAN: An implicit generative model for small
molecular graphs}},
author={De Cao, Nicola and Kipf, Thomas},
journal={ICML 2018 workshop on Theoretical Foundations
and Applications of Deep Generative Models},
year={2018}
}```