4 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 4 cited
DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder
Bjarne Pfitzner, Bert Arnrich
Federated learning (FL) is getting increased attention for processing sensitive, distributed datasets common to domains such as healthcare. Instead of directly training classificat…
stat.AP2022★ 4 cited
Analyzing Population-Level Trials as N-of-1 Trials: an Application to Gait
Lin Zhou, Juliana Schneider, Bert Arnrich +1
Studying individual causal effects of health interventions is of interest whenever intervention effects are heterogeneous between study participants. Conducting N-of-1 trials, whic…
cs.LG2022
Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Data
Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz +2
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper eval…