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Tabular Data Generation

3 methods 4 papers tagged archive 2025-07-28

Generative Adversarial Networks (GANs) are a type of generative model that use two networks, a generator to generate images and a discriminator to discriminate between real and fake, to train a model that approximates the distribution of the data. Below you can find a continuously updating list of GANs.

Methods

All 3 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.

CTAB-GAN – 2
Outlier Generation Outlier Generation in Tabular Data – 1
TabularARGN Tabular Auto-Regressive Generative Network – 1