most citeddpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation

3 citations · 3 across the 3 of their papers we have counts for

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cs.CR2025

dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation

Sofiane Mahiou, Amir Dizche, Reza Nazari +4

We propose dpmm, an open-source library for synthetic data generation with Differentially Private (DP) guarantees. It includes three popular marginal models -- PrivBayes, MST, and…

cs.CR2025

Understanding the Impact of Data Domain Extraction on Synthetic Data Privacy

Georgi Ganev, Meenatchi Sundaram Muthu Selva Annamalai, Sofiane Mahiou +1

Privacy attacks, particularly membership inference attacks (MIAs), are widely used to assess the privacy of generative models for tabular synthetic data, including those with Diffe…