Data Mining and Knowledge Discovery in Medical Applications Using Self-Organizing Maps. - Thomas Villmann; Wieland Hermann; Michael Geyer (ISMDA, 2000)

Learning Vector Quantization Classification with Local Relevance Determination for Medical Data. - Barbara Hammer; Thomas Villmann; Frank-Michael Schleif; Cornelia Albani; Wieland Hermann (ICAISC, 2006)

Fuzzy classification by fuzzy labeled neural gas. - Thomas Villmann; Barbara Hammer; Frank-Michael Schleif; Tina Geweniger; Wieland Hermann (Neural Networks, 2006)

Fuzzy classification using information theoretic learning vector quantization. - Thomas Villmann; Barbara Hammer; Frank-Michael Schleif; Wieland Hermann; Marie Cottrell (Neurocomputing, 2008)

Integration of Structural Expert Knowledge about Classes for Classification Using the Fuzzy Supervised Neural Gas. - Marika Kästner; Wieland Hermann; Thomas Villmann (ESANN, 2012)

Border-Sensitive Learning in Kernelized Learning Vector Quantization. - Marika Kästner; Martin Riedel; Marc Strickert; Wieland Hermann; Thomas Villmann (IWANN (1), 2013)

Precision-Recall-Optimization in Learning Vector Quantization Classifiers for Improved Medical Classification Systems. - Thomas Villmann; Marika Kaden; Mandy Lange; Paul Sturmer; Wieland Hermann (CIDM, 2014)

Optimization of General Statistical Accuracy Measures for Classification Based on Learning Vector Quantization. - Marika Kaden; Wieland Hermann; Thomas Villmann (ESANN, 2014)

Attention Based Classification Learning in GLVQ and Asymmetric Misclassification Assessment. - Marika Kaden; Wieland Hermann; Thomas Villmann (WSOM, 2014)

Border-sensitive learning in generalized learning vector quantization: an alternative to support vector machines. - Marika Kaden; Martin Riedel; Wieland Hermann; Thomas Villmann (Soft Comput., 2015)

Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach. - Andrea Villmann; Marika Kaden; Sascha Saralajew; Wieland Hermann; Thomas Villmann (ESANN, 2018)

Learning vector quantization classifiers for ROC-optimization. - Thomas Villmann; Marika Kaden; Wieland Hermann; Michael Biehl (Comput. Stat., 2018)

Prototype-based One-Class-Classification Learning Using Local Representations. - Daniel Staps; Ronny Schubert; Marika Kaden; Alexander Lampe; Wieland Hermann; Thomas Villmann (IJCNN, 2022)