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cs.LG2026
Flow Matching for Tabular Data Synthesis
Bahrul Ilmi Nasution, Floor Eijkelboom, Mark Elliot +2
Synthetic data generation is an important tool for privacy-preserving data sharing. Although diffusion models have set recent benchmarks, flow matching (FM) offers a promising alte…
cs.LG2026
Bayesian Generative Adversarial Networks via Gaussian Approximation for Tabular Data Synthesis
Bahrul Ilmi Nasution, Mark Elliot, Richard Allmendinger
Generative Adversarial Networks (GAN) have been used in many studies to synthesise mixed tabular data. Conditional tabular GAN (CTGAN) have been the most popular variant but strugg…
cs.LG2024
Multi-objective evolutionary GAN for tabular data synthesis
Nian Ran, Bahrul Ilmi Nasution, Claire Little +2
Synthetic data has a key role to play in data sharing by statistical agencies and other generators of statistical data products. Generative Adversarial Networks (GANs), typically a…