Private Post-GAN Boosting
Replication code for ICLR 2021 paper on differentially private synthetic data generation.
Replication code for ICLR 2021 paper on differentially private synthetic data generation.
Examining what privacy guarantees synthetic data can satisfy even without formal guarantees during synthesizer training.
Algorithms for continually releasing differentially private synthetic data from longitudinal data collections.
A general-purpose method combining bootstrap with differentially private non-parametric distribution estimation.
Differentially private method combining samples from GAN training to create high-quality synthetic data.
A framework to evaluate the quality of differentially private synthetic data from an applied researcher’s perspective.