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About us Practical matters How to find us M. (Michael) Biehl, Prof

Research interests

Machine Learning, Neural Networks, Data Analysis, Pattern Recognition, Biomedical Data, Bioinformatics, Classification, Supervised Learning, Unsupervised Learning, Computational Science, Scientific Computation, Modeling and Simulation, Statistical Physics

Publications

Hidden unit specialization in layered neural networks:: ReLU vs. sigmoidal activation

Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: A prospective test validation study

Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples

An application of generalized matrix learning vector quantization in neuroimaging

Supervised learning in the presence of concept drift: A modelling framework

Discriminative Subspace Emersion from learning feature relevances across different populations

Interpretable modelling and visualization of biomedical data

IRMA: Machine learning-based harmonization of 18F-FDG PET brain scans in multi-center studies

Phase transition analysis for shallow neural networks with arbitrary activation functions

21st SC@RUG 2024 proceedings 2023-2024