PRECODE - A Generic Model Extension to Prevent Deep Gradient Leakage. - Daniel Scheliga; Patrick Mäder; Marco Seeland (WACV, 2022)

Combining Variational Modeling with Partial Gradient Perturbation to Prevent Deep Gradient Leakage. - Daniel Scheliga; Patrick Mäder; Marco Seeland (CoRR, 2022)

Dropout Is NOT All You Need to Prevent Gradient Leakage. - Daniel Scheliga; Patrick Maeder; Marco Seeland (AAAI, 2023)

Collaboration Management for Federated Learning. - Marius Schlegel; Daniel Scheliga; Kai-Uwe Sattler; Marco Seeland; Patrick Mäder (ICDEW, 2024)

Feature-Based Dataset Fingerprinting for Clustered Federated Learning on Medical Image Data. - Daniel Scheliga; Patrick Mäder; Marco Seeland (Appl. Artif. Intell., 2024)

Privacy preserving federated learning with convolutional variational bottlenecks. - Daniel Scheliga; Patrick Mäder; Marco Seeland (Cybersecur., 2025)