3 papers
cs.LG2026
A Simulated Federated Analysis of MS-Induced Brain Lesions
Evelyn Trautmann, Joël Federer-Gsponer, Markus C. Elze +1
Federated techniques such as federated learning and federated analysis have emerged as a powerful paradigm for enabling multi-center research on sensitive clinical data while prese…
cs.LG2025
Insights into the Unknown: Federated Data Diversity Analysis on Molecular Data
Markus Bujotzek, Evelyn Trautmann, Calum Hand +1
AI methods are increasingly shaping pharmaceutical drug discovery. However, their translation to industrial applications remains limited due to their reliance on public datasets, l…
cs.LG2025
Aggregating Low Rank Adapters in Federated Fine-tuning
Evelyn Trautmann, Ian Hales, Martin F. Volk
Fine-tuning large language models requires high computational and memory resources, and is therefore associated with significant costs. When training on federated datasets, an incr…