# High-Quality Tabular Data Generation using Post-Selected VAE

arXiv: https://arxiv.org/abs/2407.13016 · HTML: https://mlsanity.com/paper/2407.13016/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 15 references that are in the map.
- First posted on arXiv 17 Jul 2024.

## Builds on (most cited first, 8 of 8)

- [Neural Discrete Representation Learning](https://mlsanity.com/paper/1711.00937/) (2017)
- [Auto-Encoding Variational Bayes](https://mlsanity.com/paper/1312.6114/) (2013)
- [Modeling Tabular data using Conditional GAN](https://mlsanity.com/paper/1907.00503/) (2019)
- [Mish: A Self Regularized Non-Monotonic Activation Function](https://mlsanity.com/paper/1908.08681/) (2019)
- [CTAB-GAN+: Enhancing Tabular Data Synthesis](https://mlsanity.com/paper/2204.00401/) (2022)
- [OCT-GAN: Neural ODE-based Conditional Tabular GANs](https://mlsanity.com/paper/2105.14969/) (2021)
- [Invertible Tabular GANs: Killing Two Birds with OneStone for Tabular Data Synthesis](https://mlsanity.com/paper/2202.03636/) (2022)
- [MargCTGAN: A "Marginally'' Better CTGAN for the Low Sample Regime](https://mlsanity.com/paper/2307.07997/) (2023)

## Abstract (arXiv)

Synthetic tabular data is becoming a necessity as concerns about data privacy intensify in the world. Tabular data can be useful for testing various systems, simulating real data, analyzing the data itself or building predictive models. Unfortunately, such data may not be available due to confidentiality issues. Previous techniques, such as TVAE (Xu et al., 2019) or OCTGAN (Kim et al., 2021), are either unable to handle particularly complex datasets, or are complex in themselves, resulting in inferior run time performance. This paper introduces PSVAE, a new simple model that is capable of producing high-quality synthetic data in less run time. PSVAE incorporates two key ideas: loss optimization and post-selection. Along with these ideas, the proposed model compensates for underrepresented categories and uses a modern activation function, Mish (Misra, 2019).