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

M. (Michael) Biehl, Prof

Full Professor (Hoogleraar) Machine learning, theory and applications

Faculty of Science and Engineering

Telephone:

+31 50 36 33997 (Phone)

+31 50 36 33800 (fax)

E-mail:

m.biehl rug.nl

Homepage ORCID Research Portal

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

Oostwal, E., Straat, M. & Biehl, M., Feb-2021, In: Physica A: Statistical Mechanics and its Applications. 564, 125517.

Research output: Contribution to journal › Article › Academic › peer-review

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

Bancos, I., Taylor, A. E., Chortis, V., Sitch, A. J., Jenkinson, C., Davidge-Pitts, C. J., Lang, K., Tsagarakis, S., Macech, M., Riester, A., Deutschbein, T., Pupovac, I. D., Kienitz, T., Prete, A., Papathomas, T. G., Gilligan, L. C., Bancos, C., Reimondo, G., Haissaguerre, M. & Marina, L., Grytaas, M. A., Sajwani, A., Langton, K., Ivison, H. E., Shackleton, C. H. L., Erickson, D., Asia, M., Palimeri, S., Kondracka, A., Spyroglou, A., Ronchi, C. L., Simunov, B., Delivanis, D. A., Sutcliffe, R. P., Tsirou, I., Bednarczuk, T., Reincke, M., Burger-Stritt, S., Feelders, R. A., Canu, L., Haak, H. R., Eisenhofer, G., Dennedy, M. C., Ueland, G. A., Ivovic, M., Tabarin, A., Terzolo, M., Quinkler, M., Kastelan, D., Fassnacht, M., Beuschlein, F., Ambroziak, U., Vassiliadi, D., O'Reilly, M. W., Young, W. F., Biehl, M., Deeks, J. J., Arlt, W. & ENSAT EURINE-ACT Investigators, Sept-2020, In: Lancet Diabetes & Endocrinology. 8, 9, p. 773-781 9 p.

Research output: Contribution to journal › Article › Academic › peer-review

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

Panda, A., Yadav, A., Yeerna, H., Singh, A., Biehl, M., Lux, M., Schulz, A., Klecha, T., Doniach, S., Khiabanian, H., Ganesan, S., Tamayo, P. & Bhanot, G., 27-Jul-2020, In: Nucleic Acids Research. 48, 13, p. 7079-7098 20 p.

Research output: Contribution to journal › Article › Academic › peer-review

An application of generalized matrix learning vector quantization in neuroimaging

van Veen, R., Gurvits, V., Kogan, R. V., Meles, S. K., de Vries, G. J., Renken, R. J., Rodriguez-Oroz, M. C., Rodriguez-Rojas, R., Arnaldi, D., Raffa, S., de Jong, B. M., Leenders, K. L. & Biehl, M., Dec-2020, In: Computer Methods and Programs in Biomedicine. 197, 11 p., 105708.

Research output: Contribution to journal › Article › Academic › peer-review

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

Straat, M., Abadi, F., Kan, Z., Göpfert, C., Hammer, B. & Biehl, M., Jan-2022, In: Neural Computing and Applications. 34, 1, p. 101-118 17 p.

Research output: Contribution to journal › Article › Academic › peer-review

Endocrine and metabolic determinants of cardiometabolic risk in mild autonomous cortisol secretion

Prete, A., Abdi, L., Canducci, M., van den Brandhof, E. L., Albors-Zumel, A., Jenkinson, C., Gilligan, L. C., Zhang, Y., Visser, L., Chortis, V., Najdekr, L., Jankevics, A., Lloyd, G. R., Winder, C. L., Tsagarakis, S., Lang, K., Macech, M., Fell, V., Vodanovic, I. D. & Reimondo, G., Marina, L. V., Deutschbein, T., Balomenaki, M., O'Reilly, M. W., Bednarczuk, T., Dusek, T., Diamantopoulos, A., Asia, M., Kondracka, A., Yu, K., Masjkur, J. R., Quinkler, M., Ueland, G. Å., Dennedy, M. C., Beuschlein, F., Tabarin, A., Fassnacht, M., Ivovic, M., Terzolo, M., Kastelan, D., Young, W. F., Manolopoulos, K. N., Ambroziak, U., Vassiliadi, D. A., Bancos, I., Sitch, A. J., Taylor, A. E., Tino, P., Biehl, M., Dunn, W. B., Arlt, W. & ENSAT EURINE-ACT Investigators, Feb-2026, In: EBioMedicine. 124, 17 p., 106126.

Research output: Contribution to journal › Article › Academic › peer-review

FA(IR)2MA-GLVQ – A hidden-feature-bias mitigation approach for fairness in classification learning based on generalized matrix learning vector quantization

Kaden, M., Schubert, R., Voigt, J., Reuss, L., Engelsberger, A., Lövdal, S., van den Brandhof, E. L., Biehl, M. & Villmann, T., 14-May-2026, In: Neurocomputing. 678, 133200.

Research output: Contribution to journal › Article › Academic › peer-review

Iterated relevance matrix analysis for improved classification and robustness in prototype-based learning schemes

Lövdal, S., van den Brandhof, E. & Biehl, M., 14-Mar-2026, In: Neurocomputing. 670, 9 p., 132474.

Research output: Contribution to journal › Article › Academic › peer-review

Aligning generalization between humans and machines

Ilievski, F., Hammer, B., van Harmelen, F., Paassen, B., Saralajew, S., Schmid, U., Biehl, M., Bolognesi, M., Dong, X. L., Gashteovski, K., Hitzler, P., Marra, G., Minervini, P., Mundt, M., Ngomo, A.-C. N., Oltramari, A., Pasi, G., Saribatur, Z. G., Serafini, L. & Shawe-Taylor, J., Shwartz, V., Skitalinskaya, G., Stachl, C., van de Ven, G. M. & Villmann, T., 15-Sept-2025, In: Nature Machine Intelligence. 7, p. 1378–1389 12 p.

Research output: Contribution to journal › Article › Academic › peer-review

Discriminative Subspace Emersion from learning feature relevances across different populations

Canducci, M., Abdi, L., Prete, A., Veen, R. J., Biehl, M., Arlt, W. & Tino, P., 2-Apr-2025, (Submitted) arXiv, 25 p.

Research output: Working paper › Preprint › Academic

All (344) publications

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