Model-Based Quantification of Left Ventricular Diastolic Function in Critically Ill Patients with Atrial Fibrillation from Routine Data: A Feasibility Study. - Nicholas Kiefer; Maximilian J. Oremek; Andreas Hoeft; Sven Zenker (Comput. Math. Methods Medicine, 2019)

A dynamic risk score for early prediction of cardiogenic shock using machine learning. - Yuxuan Hu; Albert Lui; Mark Goldstein; Mukund Sudarshan; Andrea Tinsay; Cindy Tsui; Samuel Maidman; John Medamana; Neil Jethani; Aahlad Manas Puli; Vuthy Nguy; Yindalon Aphinyanaphongs; et al. (CoRR, 2023)

Harnessing Orthogonality to Train Low-Rank Neural Networks. - Daniel Coquelin; Katharina Flügel; Marie Weiel; Nicholas Kiefer; Charlotte Debus; Achim Streit; Markus Götz (ECAI, 2024)

Model Fusion via Neuron Transplantation. - Muhammed Öz; Nicholas Kiefer; Charlotte Debus; Jasmin Hörter; Achim Streit; Markus Götz (ECML/PKDD (4), 2024)

AB-Training: A Communication-Efficient Approach for Distributed Low-Rank Learning. - Daniel Coquelin; Katherina Flügel; Marie Weiel; Nicholas Kiefer; Muhammed Öz; Charlotte Debus; Achim Streit; Markus Götz (CoRR, 2024)

A Comparative Study of Pruning Methods in Transformer-based Time Series Forecasting. - Nicholas Kiefer; Arvid Weyrauch; Muhammed Öz; Achim Streit; Markus Götz; Charlotte Debus (CoRR, 2024)