Measuring Utility and Privacy of Synthetic Genomic Data. - Bristena Oprisanu; Georgi Ganev; Emiliano De Cristofaro (CoRR, 2021)

DP-SGD vs PATE: Which Has Less Disparate Impact on GANs? - Georgi Ganev (CoRR, 2021)

Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data. - Georgi Ganev; Bristena Oprisanu; Emiliano De Cristofaro (ICML, 2022)

On Utility and Privacy in Synthetic Genomic Data. - Bristena Oprisanu; Georgi Ganev; Emiliano De Cristofaro (NDSS, 2022)

dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation. - Sofiane Mahiou; Kai Xu; Georgi Ganev (CoRR, 2022)

Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation. - Kai Xu; Georgi Ganev; Emile Joubert; Rees Davison; Olivier Van Acker; Luke Robinson (ICLR, 2023)

Understanding how Differentially Private Generative Models Spend their Privacy Budget. - Georgi Ganev; Kai Xu; Emiliano De Cristofaro (CoRR, 2023)

When Synthetic Data Met Regulation. - Georgi Ganev (CoRR, 2023)

On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise. - Lauren Arthur; Jason Costello; Jonathan Hardy; Will O'Brien; James Rea; Gareth Rees; Georgi Ganev (CoRR, 2023)

On the Inadequacy of Similarity-based Privacy Metrics: Reconstruction Attacks against "Truly Anonymous Synthetic Data". - Georgi Ganev; Emiliano De Cristofaro (CoRR, 2023)

Graphical vs. Deep Generative Models: Measuring the Impact of Differentially Private Mechanisms and Budgets on Utility. - Georgi Ganev; Kai Xu; Emiliano De Cristofaro (CCS, 2024)

"What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation. - Meenatchi Sundaram Muthu Selva Annamalai; Georgi Ganev; Emiliano De Cristofaro (USENIX Security Symposium, 2024)

The Elusive Pursuit of Replicating PATE-GAN: Benchmarking, Auditing, Debugging. - Georgi Ganev; Meenatchi Sundaram Muthu Selva Annamalai; Emiliano De Cristofaro (CoRR, 2024)

Synthetic Data, Similarity-based Privacy Metrics, and Regulatory (Non-)Compliance. - Georgi Ganev (CoRR, 2024)

The Inadequacy of Similarity-Based Privacy Metrics: Privacy Attacks Against "Truly Anonymous" Synthetic Datasets. - Georgi Ganev; Emiliano De Cristofaro (SP, 2025)

The Elusive Pursuit of Reproducing PATE-GAN: Benchmarking, Auditing, Debugging. - Georgi Ganev; Meenatchi Sundaram Muthu Selva Annamalai; Emiliano De Cristofaro (Trans. Mach. Learn. Res., 2025)

The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data. - Georgi Ganev; Meenatchi Sundaram Muthu Selva Annamalai; Sofiane Mahiou; Emiliano De Cristofaro (CoRR, 2025)

Understanding the Impact of Data Domain Extraction on Synthetic Data Privacy. - Georgi Ganev; Meenatchi Sundaram Muthu Selva Annamalai; Sofiane Mahiou; Emiliano De Cristofaro (CoRR, 2025)

The DCR Delusion: Measuring the Privacy Risk of Synthetic Data. - Zexi Yao; Natasa Krco; Georgi Ganev; Yves-Alexandre de Montjoye (CoRR, 2025)

dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation. - Sofiane Mahiou; Amir Dizche; Reza Nazari; Xinmin Wu; Ralph Abbey; Jorge Silva; Georgi Ganev (CoRR, 2025)