3 papers
cs.LG2025
Privacy Preserving Diffusion Models for Mixed-Type Tabular Data Generation
Timur Sattarov, Marco Schreyer, Damian Borth
We introduce DP-FinDiff, a differentially private diffusion framework for synthesizing mixed-type tabular data. DP-FinDiff employs embedding-based representations for categorical f…
cs.LG2025
Federated Diffusion Modeling with Differential Privacy for Tabular Data Synthesis
Timur Sattarov, Marco Schreyer, Damian Borth
The increasing demand for privacy-preserving data analytics in various domains necessitates solutions for synthetic data generation that rigorously uphold privacy standards. We int…
cs.LG2025
Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data
Timur Sattarov, Marco Schreyer, Damian Borth
Anomaly detection in tabular data remains challenging due to complex feature interactions and the scarcity of anomalous examples. Denoising autoencoders rely on fixed-magnitude noi…