Skip to content

Add TabGAN - synthetic tabular data generation with GANs, Diffusion, and LLMs#3003

Merged
JinyangWang27 merged 2 commits intovinta:masterfrom
Diyago:add-tabgan
Mar 29, 2026
Merged

Add TabGAN - synthetic tabular data generation with GANs, Diffusion, and LLMs#3003
JinyangWang27 merged 2 commits intovinta:masterfrom
Diyago:add-tabgan

Conversation

@Diyago
Copy link
Copy Markdown
Contributor

@Diyago Diyago commented Mar 28, 2026

Add TabGAN — Synthetic Tabular Data Generation

TabGAN is a Python library for generating high-quality synthetic tabular data using multiple generative approaches through a unified API:

  • CTGAN (Conditional Tabular GAN) for mixed data types
  • ForestDiffusion (tree-based diffusion) for structured data
  • GReaT (Large Language Models) for semantic dependencies

Key Features

  • Unified API across GANs, Diffusion Models, and LLMs
  • Adversarial filtering ensures distribution consistency
  • Privacy metrics (DCR, NNDR, membership inference)
  • Constraint enforcement (range, uniqueness, formula, regex)
  • HTML quality reports with distribution comparisons
  • sklearn TabGANTransformer for Pipeline integration
  • 100K+ PyPI downloads, 115 tests, Apache 2.0

Paper: Tabular GANs for uneven distribution

Copy link
Copy Markdown
Collaborator

@JinyangWang27 JinyangWang27 left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Can you remove the additional empty line? Then it will be ready to merge.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
@Diyago
Copy link
Copy Markdown
Contributor Author

Diyago commented Mar 29, 2026

image

fixed

@Diyago Diyago requested a review from JinyangWang27 March 29, 2026 07:23
@JinyangWang27 JinyangWang27 merged commit 9084be2 into vinta:master Mar 29, 2026
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants