GRDM jointly generates relational database tables via graph-conditional diffusion without table ordering, outperforming autoregressive baselines on multi-hop correlations and single-table fidelity across six real RDBs.
Beyond privacy: Navigating the opportunities and challenges of synthetic data
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The MIDST challenge evaluated privacy resilience of diffusion-generated synthetic tabular data via membership inference attacks and produced new black-box and white-box attack methods.
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Joint Relational Database Generation via Graph-Conditional Diffusion Models
GRDM jointly generates relational database tables via graph-conditional diffusion without table ordering, outperforming autoregressive baselines on multi-hop correlations and single-table fidelity across six real RDBs.
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MIDST Challenge at SaTML 2025: Membership Inference over Diffusion-models-based Synthetic Tabular data
The MIDST challenge evaluated privacy resilience of diffusion-generated synthetic tabular data via membership inference attacks and produced new black-box and white-box attack methods.