https://github.com/rajeevatla/supercongan

Training a GAN using superconductivity data
https://github.com/rajeevatla/supercongan

gan generative-adversarial-network superconductivity superconductivity-data superconductivity-dataset superconductor-simulation-data superconductors synthetic-dataset-generation tabular-data

Last synced: 8 months ago
JSON representation

Training a GAN using superconductivity data

• Host: GitHub
• URL: https://github.com/rajeevatla/supercongan
• Owner: RajeevAtla
• License: mit
• Created: 2020-09-18T00:26:27.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2024-02-01T21:14:01.000Z (over 2 years ago)
• Last Synced: 2025-02-15T12:42:19.563Z (over 1 year ago)
• Topics: gan, generative-adversarial-network, superconductivity, superconductivity-data, superconductivity-dataset, superconductor-simulation-data, superconductors, synthetic-dataset-generation, tabular-data
• Language: TeX
• Homepage:
• Size: 724 KB
• Stars: 5
• Watchers: 1
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# SuperconGAN

[![Downloads](https://static.pepy.tech/personalized-badge/supercongan?period=total&units=international_system&left_color=black&right_color=blue&left_text=Downloads)](https://pepy.tech/project/supercongan)

A program to train a GAN using superconductivity data.

It was inspired by and is based off of the CTGAN library for generating GANs for tabular datasets.

## Installation

To install the latest version, please use the following command in a terminal window:

```PowerShell

python3 -m pip install SuperconGAN --upgrade

```

## Starter Example

To get a feel for the package, try running the following code, after installing the package (above):

```python

import SuperconGAN

model = SuperconGAN.Synthesizer()

model.fit(epochs = 5)

model.sample(n = 10)

```

## Documentation

Will be added shortly.