The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Generative Adversarial Networks are applied to generate generative data for a data source. A generative model consisting of a generator and a discriminator network is trained. During iterative training the distribution of generated data is converging to that of the data source. Direct applications of generative data are the created functions for data evaluation and missing data completion. A software service for accelerated training of generative models on graphics processing units is available. Reference: Goodfellow et al. (2014) <doi:10.48550/arXiv.1406.2661>.
| Version: | 2.1.3 |
| Imports: | Rcpp (≥ 1.0.3), tensorflow (≥ 2.0.0), httr (≥ 1.4.7) |
| LinkingTo: | Rcpp |
| Published: | 2024-10-07 |
| DOI: | 10.32614/CRAN.package.ganGenerativeData |
| Author: | Werner Mueller [aut, cre] |
| Maintainer: | Werner Mueller <werner.mueller5 at chello.at> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| SystemRequirements: | TensorFlow (https://www.tensorflow.org) |
| CRAN checks: | ganGenerativeData results |
| Reference manual: | ganGenerativeData.pdf |
| Package source: | ganGenerativeData_2.1.3.tar.gz |
| Windows binaries: | r-devel: ganGenerativeData_2.1.3.zip, r-release: ganGenerativeData_2.1.3.zip, r-oldrel: ganGenerativeData_2.1.3.zip |
| macOS binaries: | r-release (arm64): ganGenerativeData_2.1.3.tgz, r-oldrel (arm64): ganGenerativeData_2.1.3.tgz, r-release (x86_64): ganGenerativeData_2.1.3.tgz, r-oldrel (x86_64): ganGenerativeData_2.1.3.tgz |
| Old sources: | ganGenerativeData archive |
Please use the canonical form https://CRAN.R-project.org/package=ganGenerativeData to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.