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Michael Biehl

Affiliations:	1988-1992	Physics	Unviversity of Gießen, Germany
	1992-2003	Theoretical Physics	University of Würzburg, Würzburg, Bayern, Germany
	2003-	Johann Bernoulli Institute for Mathematics and Computer Science	University of Groningen, Groningen, Netherlands

Area:

Statistical Physics, Machine Learning

Parents

Wolfgang Kinzel	grad student	1988-1992	Justus-Liebig-Universität Gießen
(PhD completed in 1992)

Children

Otavio Cistolo Citton	grad student		RUG
Martin Ahr	grad student	2002
Christoph Bunzmann	grad student	2003
Florian Much	grad student	2004	University of Wurzburg
Thorsten Volkmann	grad student	2004	University of Wurzburg
Anarta Ghosh	grad student	2007	RUG
Markus Walther	grad student	2008	University of Wurzburg
Sebastian Weber	grad student	2008	University of Wurzburg
Petra Schneider	grad student	2006-2010	RUG
Aree Witoelar	grad student	2006-2010	RUG
Kerstin Bunte	grad student	2007-2011	RUG
Tina Geweniger	grad student	2012	RUG
Dietlind Zühlke	grad student	2012	RUG
Sven Haase	grad student	2014	RUG
Gert-Jan de Vries	grad student	2014	RUG
Ernest Mwebaze	grad student	2009-2014	RUG
Deborah Mudali	grad student	2016	RUG
Matthias Gay	grad student	2017	RUG
Mandy Lange-Geisler	grad student	2019	RUG
David Nebel	grad student	2015-2020	RUG
Godliver Owomugisha	grad student	2015-2020	RUG

Collaborators

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Publications

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van Veen R, Tamboli NRB, Lövdal S, et al. (2024) Subspace corrected relevance learning with application in neuroimaging. Artificial Intelligence in Medicine. 149: 102786
Htun HH, Biehl M, Petkov N. (2023) Survey of feature selection and extraction techniques for stock market prediction. Financial Innovation. 9: 26
van Veen R, Gurvits V, Kogan RV, et al. (2020) An application of generalized matrix learning vector quantization in neuroimaging. Computer Methods and Programs in Biomedicine. 197: 105708
Owomugisha G, Mugagga PKB, Melchert F, et al. (2020) A low-cost 3-D printed smartphone add-on spectrometer for diagnosis of crop diseases in field. The Compass. 331-332
Pfannschmidt L, Jakob J, Hinder F, et al. (2020) Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information Neurocomputing
Nolte A, Wang L, Bilicki M, et al. (2019) Galaxy classification: A machine learning analysis of GAMA catalogue data Neurocomputing. 342: 172-190
Melchert F, Bani G, Seiffert U, et al. (2019) Adaptive basis functions for prototype-based classification of functional data Neural Computing and Applications. 1-11
Straat M, Kaden M, Villmann T, et al. (2019) Learning vector quantization and relevances in complex coefficient space Neural Computing and Applications. 1-15
Straat M, Abadi F, Göpfert C, et al. (2018) Statistical Mechanics of On-Line Learning Under Concept Drift. Entropy (Basel, Switzerland). 20
Straat M, Abadi F, Göpfert C, et al. (2018) Statistical Mechanics of On-Line Learning Under Concept Drift Entropy. 20: 775

Michael Biehl

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