most citedReal World Federated Learning with a Knowledge Distilled Transformer for Cardiac CT Imaging

4 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2024

FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels

Malte Tölle, Fernando Navarro, Sebastian Eble +3

Federated learning is one popular paradigm to train a joint model in a distributed, privacy-preserving environment. But partial annotations pose an obstacle meaning that categories…

eess.IV2024★ 4 cited

Real World Federated Learning with a Knowledge Distilled Transformer for Cardiac CT Imaging

Malte Tölle, Philipp Garthe, Clemens Scherer +22

Federated learning is a renowned technique for utilizing decentralized data while preserving privacy. However, real-world applications often face challenges like partially labeled…