Kristian Schwethelm

According to our database, Kristian Schwethelm authored at least 10 papers between 2023 and 2026.

Collaborative distances:

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

2026

Beyond privacy: the potentialities of differential privacy in generative AI.

Jonas Kuntzer, Johannes Kaiser, Tamara T. Mueller, Anneliese Riess, Kristian Schwethelm, Georgios Kaissis, Daniel Rueckert

Discov. Artif. Intell., December, 2026

How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models.

Kristian Schwethelm, Daniel Rueckert, Georgios Kaissis

CoRR, April, 2026

2025

On Arbitrary Predictions from Equally Valid Models.

Sarah Lockfisch, Kristian Schwethelm, Martin J. Menten, Rickmer Braren, Daniel Rueckert, Alexander Ziller, Georgios Kaissis

CoRR, July, 2025

Visual Privacy Auditing with Diffusion Models.

Kristian Schwethelm, Johannes Kaiser, Moritz Knolle, Sarah Lockfisch, Daniel Rueckert, Alexander Ziller

Trans. Mach. Learn. Res., 2025

Differentially Private Active Learning: Balancing Effective Data Selection and Privacy.

Kristian Schwethelm, Johannes Kaiser, Jonas Kuntzer, Mehmet Yigitsoy, Daniel Rückert, Georgios Kaissis

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2025

Laplace Sample Information: Data Informativeness Through a Bayesian Lens.

Johannes Kaiser, Kristian Schwethelm, Daniel Rueckert, Georgios Kaissis

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Visual Privacy Auditing with Diffusion Models.

Kristian Schwethelm, Johannes Kaiser, Moritz Knolle, Daniel Rueckert, Georgios Kaissis, Alexander Ziller

CoRR, 2024

Bounding Reconstruction Attack Success of Adversaries Without Data Priors.

Alexander Ziller, Anneliese Riess, Kristian Schwethelm, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis

CoRR, 2024

Fully Hyperbolic Convolutional Neural Networks for Computer Vision.

Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Hyperbolic Geometry in Computer Vision: A Novel Framework for Convolutional Neural Networks.

Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr

CoRR, 2023