Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices. - Mohammad Mohammadi; Michael Biehl; Andrea Villmann; Thomas Villmann (ICAISC (1), 2017)

Fusion of deep learning architectures, multilayer feedforward networks and learning vector quantizers for deep classification learning. - Thomas Villmann; Michael Biehl; Andrea Villmann; Sascha Saralajew (WSOM, 2017)

Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning. - David Nebel; Marika Kaden; Andrea Villmann; Thomas Villmann (Neurocomputing, 2017)

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)

Probabilistic Learning Vector Quantization with Cross-Entropy for Probabilistic Class Assignments in Classification Learning. - Andrea Villmann; Marika Kaden; Sascha Saralajew; Thomas Villmann (ICAISC (1), 2018)

Appropriate Data Density Models in Probabilistic Machine Learning Approaches for Data Analysis. - Thomas Villmann; Marika Kaden; Mehrdad Mohannazadeh Bakhtiari; Andrea Villmann (ICAISC (2), 2019)

Searching for the Origins of Life - Detecting RNA Life Signatures Using Learning Vector Quantization. - Thomas Villmann; Marika Kaden; Szymon Wasik; Mateusz Kudla; Kaja Gutowska; Andrea Villmann; Jacek Blazewicz (WSOM+, 2019)

Investigation of Activation Functions for Generalized Learning Vector Quantization. - Thomas Villmann; Jensun Ravichandran; Andrea Villmann; David Nebel; Marika Kaden (WSOM+, 2019)

Activation Functions for Generalized Learning Vector Quantization - A Performance Comparison. - Thomas Villmann; John Ravichandran; Andrea Villmann; David Nebel; Marika Kaden (CoRR, 2019)

Quantum-Inspired Learning Vector Quantization for Classification Learning. - Thomas Villmann; Jensun Ravichandran; Alexander Engelsberger; Andrea Villmann; Marika Kaden (ESANN, 2020)

Quantum-inspired learning vector quantizers for prototype-based classification. - Thomas Villmann; Alexander Engelsberger; Jensun Ravichandran; Andrea Villmann; Marika Kaden (Neural Comput. Appl., 2022)

The Geometry of Decision Borders Between Affine Space Prototypes for Nearest Prototype Classifiers. - Mehrdad Mohannazadeh Bakhtiari; Andrea Villmann; Thomas Villmann (ICAISC (1), 2023)