6 citations · 6 across the 3 of their papers we have counts for
6 papers
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…
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…
MAPEX: Modality-Aware Pruning of Experts for Remote Sensing Foundation Models
Joelle Hanna, Linus Scheibenreif, Damian Borth
Remote sensing data is commonly used for tasks such as flood mapping, wildfire detection, or land-use studies. For each task, scientists carefully choose appropriate modalities or…
Know Your Attention Maps: Class-specific Token Masking for Weakly Supervised Semantic Segmentation
Joelle Hanna, Damian Borth
Weakly Supervised Semantic Segmentation (WSSS) is a challenging problem that has been extensively studied in recent years. Traditional approaches often rely on external modules lik…
SAR-to-RGB Translation with Latent Diffusion for Earth Observation
Kaan Aydin, Joelle Hanna, Damian Borth
Earth observation satellites like Sentinel-1 (S1) and Sentinel-2 (S2) provide complementary remote sensing (RS) data, but S2 images are often unavailable due to cloud cover or data…
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…