Author

B. Eskofier

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Open access Oct 2026

Beat-to-beat aortic valve opening detection from impedance cardiography using machine learning

Accurate detection of the aortic valve opening, represented by the B-point in the impedance cardiogram (ICG), is a critical step in non-invasive hemodynamic monitoring. The B-point is essential for deriving key parameters like the pre-ejection period (PEP) and left ventricular ejection time (LVET). However, accurat...

L. Abel, Sebastian Stühler, T. Steigleder et al. · Frontiers in Digital Health · 0 citations

#machine learning Preprint Sep 2026

Multi-center Medical Data Mining with FL-Net - A One-stop Shop for Federated Learning

Federated learning enables collaborative training without sharing patient-level data, but most studies remain simulations. Based on five requirements derived from the literature, we analyzed 14 FL frameworks and found that none fully satisfied these requirements. We present FL-Net, a novel federated clinical research f...

Simon Süwer, Juliane Klemm, E. Acitelli et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Not All Nodes Are Created Equal: Homophily-Aware Stratification for Stable GNN Evaluation

Graph neural networks are widely used for transductive node classification, with accuracy typically measured on randomly drawn train/validation/test splits. Reported accuracy has been shown to shift substantially across different random splits of the same dataset, making published comparisons between architectures unre...

Naga Venkata Sai Jitin Jami, Thomas R. Altstidl, S. Hoefler et al. · 0 citations

#computer vision Preprint Sep 2026

Do Depressive Facial Patterns Transfer Across Cultures and Contexts? Evidence from a German RCT and E-DAIC

Automated assessment of depression from facial dynamics holds promise for scalable mental health monitoring, yet cross-corpus generalization of learned biomarkers remains an open challenge. We present a systematic bidirectional transfer study pairing the EmpkinS-EKSpression randomized controlled trial (RCT; N = 256, SC...

Misha Sadeghi, R. Richer, L. H. Rupp et al. · 0 citations

#natural language process... Preprint Sep 2026

How LLMs Build Fictional Worlds: Setting and Narrative Space in AI-Generated Creative Storytelling

This paper compares 1,000 AI-generated stories per model in English and German with human-authored fiction from Project Gutenberg to find that human-authored texts predominantly employ "action space,"grounding narratives in embodied character-environment interaction, whereas LLMs systematically overproduce "perceived s...

Katrin Rohrbacher, Björn Nieth, Emmanuelle Salin et al. · 0 citations

Preprint Aug 2026

You Only Flow Once: Calibrated and Real-Time Radar Pose Estimation with Multi-Hypothesis Normalizing Flows

This work proposes Multi-Hypothesis Normalizing Flow Pose Generator (MH-NFPG), which models pose distributions from radar point clouds using a conditional normalizing flow that transforms a Laplace base distribution into an expressive posterior, generated in parallel through a single forward pass.

J. Mueller, S. Hoefler, D. Zanca et al. · 0 citations

#natural language process... May 2026

How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework

This work proposes a context-aware evaluation framework in which human-likeness is assessed using a two-sample problem between the linguistic feature distribution of a human reference corpus for a given register and a corresponding LLM-generated corpus.

Björn Nieth, Marianna Gracheva, Michaela Mahlberg et al. · arXiv.org · 0 citations