Package: RGAN
Title: Generative Adversarial Nets (GAN) in R
Version: 0.2.2
Authors@R: 
    person(given = "Marcel",
           family = "Neunhoeffer",
           role = c("aut", "cre"),
           email = "marcel.neunhoeffer@gmail.com",
           comment = c(ORCID = "0000-0002-9137-5785"))
Description: 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.
License: MIT + file LICENSE
URL: https://github.com/mneunhoe/RGAN
BugReports: https://github.com/mneunhoe/RGAN/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Imports: cli, R6, torch, viridis
Suggests: opendp, rmarkdown, knitr, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
Repository: https://mneunhoe.r-universe.dev
Date/Publication: 2026-09-15 13:27:53 UTC
RemoteUrl: https://github.com/mneunhoe/rgan
RemoteRef: HEAD
RemoteSha: fe64f21fd23b52de03b718277de8136adcaf2616
NeedsCompilation: no
Packaged: 2026-10-15 11:14:40 UTC; root
Author: Marcel Neunhoeffer [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-9137-5785>)
Maintainer: Marcel Neunhoeffer <marcel.neunhoeffer@gmail.com>