RGAN
Generative Adversarial Nets (GAN) in R
An easy way to get started with Generative Adversarial Nets (GAN) in R. The GAN algorithm was initially described by Goodfellow et al. 2014 <https://proceedings.neurips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf>. A GAN can be used to learn the joint distribution of complex data by comparison. A GAN consists of two neural networks a Generator and a Discriminator, where the two neural networks play an adversarial minimax game. Built-in GAN models make the training of GANs in R possible in one line and make it easy to experiment with different design choices (e.g. different network architectures, value functions, optimizers). The built-in GAN models work with tabular data (e.g. to produce synthetic data) and image data. Methods to post-process the output of GAN models to enhance the quality of samples are available.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | RGAN_0.1.1.tar.gz |
248.2 KiB |
0.1.1 |
rolling linux/noble R-4.5 | RGAN_0.1.1.tar.gz |
248.1 KiB |
0.1.1 |
rolling source/ R- | RGAN_0.1.1.tar.gz |
126.3 KiB |
0.1.1 |
latest linux/jammy R-4.5 | RGAN_0.1.1.tar.gz |
248.2 KiB |
0.1.1 |
latest linux/noble R-4.5 | RGAN_0.1.1.tar.gz |
248.1 KiB |
0.1.1 |
latest source/ R- | RGAN_0.1.1.tar.gz |
126.3 KiB |
0.1.1 |
2026-04-26 source/ R- | RGAN_0.1.1.tar.gz |
126.3 KiB |
0.1.1 |
2026-04-23 source/ R- | RGAN_0.1.1.tar.gz |
126.3 KiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | RGAN_0.1.1.zip |
250.9 KiB |
0.1.1 |
2025-04-20 source/ R- | RGAN_0.1.1.tar.gz |
126.3 KiB |