mahmoodm2 / tableGAN
tableGAN is a synthetic data generation technique (Data Synthesis based on Generative Adversarial Networks paper) based on Generative Adversarial Network architecture (DCGAN).
☆143Updated 5 years ago
Alternatives and similar repositories for tableGAN:
Users that are interested in tableGAN are comparing it to the libraries listed below
- Generative adversarial training for generating synthetic tabular data.☆284Updated 2 years ago
- Official git for "CTAB-GAN: Effective Table Data Synthesizing"☆83Updated last year
- We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review …☆540Updated last month
- Evaluate real and synthetic datasets against each other☆86Updated last month
- Benchmarking synthetic data generation methods.☆267Updated this week
- Official GitHub for CTAB-GAN+☆73Updated 9 months ago
- Generating Tabular Synthetic Data using State of the Art GAN architecture☆79Updated 4 years ago
- ☆63Updated 2 years ago
- Repository for the results of my master thesis, about the generation and evaluation of synthetic data using GANs☆44Updated last year
- A toolbox for differentially private data generation☆129Updated last year
- Metrics to evaluate quality and efficacy of synthetic datasets.☆222Updated this week
- Conditional GAN for generating synthetic tabular data.☆1,326Updated this week
- Standardised Metrics and Methods for Synthetic Tabular Data Evaluation☆29Updated 6 months ago
- A library of Reversible Data Transforms☆123Updated this week
- COR-GAN: Correlation-Capturing Convolutional Neural Networks for Generating Synthetic Healthcare Records☆57Updated 4 years ago
- Source code of paper "Differentially Private Generative Adversarial Network"☆69Updated 6 years ago
- [ICML 2023] The official implementation of the paper "TabDDPM: Modelling Tabular Data with Diffusion Models"☆420Updated 7 months ago
- Time-series Generative Adversarial Networks (fork from the ML-AIM research group on bitbucket))☆116Updated 3 years ago
- ☆105Updated last year
- ☆20Updated 6 months ago
- Official git for "TabuLa: Harnessing Language Models for Tabular Data Synthesis"☆37Updated 3 months ago
- [IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions☆303Updated last year
- Machine Learning and Artificial Intelligence for Medicine.☆438Updated last year
- ☆18Updated 5 years ago
- Explaining Anomalies Detected by Autoencoders Using SHAP☆40Updated 3 years ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆33Updated 6 years ago
- A novel approach for synthesizing tabular data using pretrained large language models☆296Updated 3 months ago
- Supplemental Material for the ESANN 2019 Submission "Preserving privacy using synthetic data models and applications in health informatic…☆19Updated 4 years ago
- Differentially-private Wasserstein GAN implementation in PyTorch☆27Updated 5 years ago
- ☆52Updated 4 years ago