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Controllable Tabular Data Synthesis Using Diffusion Models

Summary: Unconditional tabular diffusion is learned, with lightweight controllers enforcing user-defined conditions (fixed attributes, cross-table correlations). A correlation-aware sampler preserves realism under control, delivering SOTA results. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6837
Venue
SIGMOD
Year
2024
Pagerank
4.4937074e-05
Overall Rank
8,523 | 40.71%
DOI
10.1145/3639283

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Rank Citing Paper Year Venue Pagerank
10,128 WaveStitch: Flexible and Fast Conditional Time Series Generation With Diffusion Models 2026 SIGMOD 4.1945683e-05
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