RGAN: Generative Adversarial Networks in R
R package for training Generative Adversarial Networks, available on CRAN with 10,000+ downloads.
GANs
Private Post-GAN Boosting
Replication code for ICLR 2021 paper on differentially private synthetic data generation.
Method or Implementation? A Plea for More Rigor in Synthetic Data Benchmarking
Benchmarks that find GANs uncompetitive for tabular synthetic data often compare a default implementation, not the method.
Using Prior Knowledge to Improve GANs for Tabular Data Without Compromising Privacy
Three ways to build prior knowledge about the data into GANs for private tabular synthetic data, with differential privacy.
An Introduction to Generative Adversarial Nets in R: The RGAN Package
Introduces GANs to R users and presents the RGAN package, which runs on torch and makes GAN design choices easy to vary.