Tabular Data Generation
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Benchmarks
Most implemented
Modeling Tabular data using Conditional GAN
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
TabuLa: Harnessing Language Models for Tabular Data Synthesis
TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data
Papers
Generating Benchmark Health Data Using a Tabular Diffusion Transformer
Cross-Tabular Data Generation (CTDG) seeks to learn a generative model from multiple heterogeneous tables and produce new synthetic tabular datasets. However, existing synthetic tabular data generation methods are largel…
Tabular Data GenerationTDGT: A Tabular Data Generation Toolkit supporting adaptive GPU-accelerated Bayesian mixture models, diffusion-based models, and latent-space generative modeling
The growing demand for privacy-preserving data sharing has positioned synthetic data generation as a critical component of responsible AI workflows. Despite notable advances in generative modeling, existing solutions oft…
Synthetic Data GenerationTabular Data GenerationPSyGenTAB: A Privacy-Preserving Framework for Synthetic Clinical Tabular Data Generation via Constrained Optimization
The development of medical AI is constrained by limited access to high-quality clinical data due to institutional silos and strict privacy regulations such as HIPAA and GDPR. Synthetic data generation offers a potential …
Synthetic Data GenerationTabular Data GenerationBSTabDiff: Block-Subunit Diffusion Priors for High-Dimensional Tabular Data Generation
High-Dimensional Low-Sample Size (HDLSS) tabular domains (e.g., omics) are characterized by $n \ll m$, where $n$ = number of samples, and $m$ = number of features. Such domains often exhibit strong local correlation grou…
Tabular Data GenerationDifferentially Private Synthetic Data via APIs 4: Tabular Data
This paper investigates the problem of generating synthetic tabular data with differential privacy (DP) guarantees, enabling data sharing in sensitive domains. Despite extensive study, state-of-the-art methods often focu…
Tabular Data GenerationHierarchical Synthetic Tabular Data Generation: A Hybrid Top-Down and Bottom-Up Framework
Existing approaches for synthetic tabular data generation are based on either purely generative models or LLMs, both of which struggle with data heterogeneity, logical consistency, rare-event coverage, and robustness in …
Synthetic Data GenerationTabular Data Generation