University of Groningen

machine learning learning vector quantization supervised learning relevance learning tumor classification neural networks prototype-based systems statistical physics of learning interpretable machine learning phase transitions self-organizing maps explainable ai adrenal tumors biomedical data unsupervised learning artificial intelligence steroid metabolomics learning curves endocrinology adrenal tumours classification metric learning neurodegenerative disease gmlvq classfication cytokine expression t-sne feature selection cancer layered neural networks gene expression data regression bioinformatics disordered systems activation functions fdg-pet distance based classifiers parkinson tissue-specific ribosome hidden units life-sciences prototype based systems gene expression mrna proteins student teacher model species translation proteomics systems biology brain-inspired computing prototype based systesm neuroimaging brain scan data risk prediction galaxy classification astroinformatics biomarker learning theory data science learning from examples learning of a rule hidden unit specialization life science data rheumatoid athritis transfer learning lvq ssm/pca multi-source data translational medicine xai metabolomics tumour classification relevance matrix primary aldosteronism aldosteronism hormones steroids ribosomae u-map sigmoidal relu adaptive distance measures rheumatoid arthritis pet scan brain images medical data learning vector quantizaation prototype-ba feedforward networks deep learning annealed approximation ribosome ribosomal proteins selforganizing map pca ribosome composition statistical physics statistical mechanics