Michael Biehl

University of Groningen

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Articles (22)

Collaborators (8)

Fredrik Karpe

Professor of Metabolic Medicine

University of Oxford

UNITED KINGDOM

Maria C. Rodríguez‐Oroz

Marina AJ Tijssen

professor Movement Disorders

University of Groningen

Marianna Bolognesi

University of Bologna

Sreejita Ghosh

Eindhoven University of Technology

Barbara Hammer

Professor at University of Bielefeld

Bielefeld University

Kerstin Bunte

Professor at University of Groningen

University of Groningen

Klaus Leonhard Leenders

Universitair Medisch Centrum Utrecht

Michael Biehl

Research Interests

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Contact this professor

Articles (22)

Collaborators (8)

Fredrik Karpe

Maria C. Rodríguez‐Oroz

Marina AJ Tijssen

Marianna Bolognesi

Sreejita Ghosh

Barbara Hammer

Kerstin Bunte

Klaus Leonhard Leenders

How do I reach out?

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Michael Biehl

Research Interests

Explore related searches

Contact this professor

Articles (22)

Hermite polynomials facilitating on-line learning analysis of layered neural networks with arbitrary activation function

Aligning generalization between humans and machines

Explainable machine learning for movement disorders - Classification of tremor and myoclonus

Interpretable modelling and visualization of biomedical data

IRMA

Phase transition analysis for shallow neural networks with arbitrary activation functions

Iterated Relevance Matrix Analysis (IRMA) for the identification of class-discriminative subspaces

Investigating the aspect of asymmetry in brain-first versus body-first Parkinson’s disease

Subspace corrected relevance learning with application in neuroimaging

Urine steroid metabolomics as a diagnostic tool in primary aldosteronism

Translating the potential of the urine steroid metabolome to stage NAFLD (TrUSt-NAFLD)

Forecasting Relative Returns for S&P 500 Stocks Using Machine Learning

Survey of Feature Selection and Extraction Techniques for Stock Market Prediction

A machine learning based approach to gravitational lens identification with the International LOFAR Telescope

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

DECORAS

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

Comment on "A Modern Assessment of Cancer Risk in Adrenal Incidentalomas

Hidden unit specialization in layered neural networks:

Matrix Relevance Learning From Spectral Data for Diagnosing Cassava Diseases

An application of generalized matrix learning vector quantization in neuroimaging.

Adaptive basis functions for prototype-based classification of functional data

Collaborators (8)

Fredrik Karpe

Maria C. Rodríguez‐Oroz

Marina AJ Tijssen

Marianna Bolognesi

Sreejita Ghosh

Barbara Hammer

Kerstin Bunte

Klaus Leonhard Leenders

How do I reach out?

Meet Kite AI