Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
A Sobering Look at Tabular Data Generation via Probabilistic Circuits
Davide Scassola, Dylan Ponsford, Adrián Javaloy +4
Tabular data is more challenging to generate than text and images, due to its heterogeneous features and much lower sample sizes. On this task, diffusion-based models are the curre…
cs.LG2025
Graph-Conditional Flow Matching for Relational Data Generation
Davide Scassola, Sebastiano Saccani, Luca Bortolussi
Data synthesis is gaining momentum as a privacy-enhancing technology. While single-table tabular data generation has seen considerable progress, current methods for multi-table dat…
cs.LG2025
Contrastive Learning-Based privacy metrics in Tabular Synthetic Datasets
Milton Nicolás Plasencia Palacios, Sebastiano Saccani, Gabriele Sgroi +2
Synthetic data has garnered attention as a Privacy Enhancing Technology (PET) in sectors such as healthcare and finance. When using synthetic data in practical applications, it is…