AINeutralarXiv – CS AI · 18h ago6/10
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BSTabDiff: Block-Subunit Diffusion Priors for High-Dimensional Tabular Data Generation
Researchers introduce BSTabDiff, a generative framework designed to create synthetic high-dimensional tabular data with limited samples by partitioning features into latent blocks and using diffusion priors. The method addresses challenges in domains like genomics where data is sparse relative to feature count, producing more realistic synthetic data than existing approaches.