# On the Performance of Generative Adversarial Network (GAN) Variants: A Clinical Data Study

arXiv: https://arxiv.org/abs/2009.09579 · HTML: https://mlsanity.com/paper/2009.09579/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Sep 2020.

## Built on by (most cited first, 1 of 1)

- [Synthetic Data Generation for Augmenting Small Samples](https://mlsanity.com/paper/2501.18741/) (2025)

## Abstract (arXiv)

Generative Adversarial Network (GAN) is a useful type of Neural Networks in various types of applications including generative models and feature extraction. Various types of GANs are being researched with different insights, resulting in a diverse family of GANs with a better performance in each generation. This review focuses on various GANs categorized by their common traits.