Daniel Scheliga

According to our database, Daniel Scheliga authored at least 6 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Privacy preserving federated learning with convolutional variational bottlenecks.

Daniel Scheliga, Patrick Mäder, Marco Seeland

Cybersecur., December, 2025

2024

Feature-Based Dataset Fingerprinting for Clustered Federated Learning on Medical Image Data.

Daniel Scheliga, Patrick Mäder, Marco Seeland

Appl. Artif. Intell., December, 2024

Collaboration Management for Federated Learning.

Marius Schlegel, Daniel Scheliga, Kai-Uwe Sattler, Marco Seeland, Patrick Mäder

Proceedings of the 40th International Conference on Data Engineering, ICDE 2024, 2024

2023

Dropout Is NOT All You Need to Prevent Gradient Leakage.

Daniel Scheliga, Patrick Maeder, Marco Seeland

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Combining Variational Modeling with Partial Gradient Perturbation to Prevent Deep Gradient Leakage.

Daniel Scheliga, Patrick Mäder, Marco Seeland

CoRR, 2022

PRECODE - A Generic Model Extension to Prevent Deep Gradient Leakage.

Daniel Scheliga, Patrick Mäder, Marco Seeland

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022