Andrea Villmann

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 12

Top Topics

Learning Vector Quantization

Neural Architecture

Classification Decisions

Top Venues

Publications

Mehrdad Mohannazadeh Bakhtiari, Andrea Villmann, Thomas Villmann
The Geometry of Decision Borders Between Affine Space Prototypes for Nearest Prototype Classifiers. ICAISC (1) (2023)
Thomas Villmann, Alexander Engelsberger, Jensun Ravichandran, Andrea Villmann, Marika Kaden
Quantum-inspired learning vector quantizers for prototype-based classification. Neural Comput. Appl. 34 (1) (2022)
Thomas Villmann, Jensun Ravichandran, Alexander Engelsberger, Andrea Villmann, Marika Kaden
Quantum-Inspired Learning Vector Quantization for Classification Learning. ESANN (2020)
Thomas Villmann, Marika Kaden, Szymon Wasik, Mateusz Kudla, Kaja Gutowska, Andrea Villmann, Jacek Blazewicz
Searching for the Origins of Life - Detecting RNA Life Signatures Using Learning Vector Quantization. WSOM+ (2019)
Thomas Villmann, Marika Kaden, Mehrdad Mohannazadeh Bakhtiari, Andrea Villmann
Appropriate Data Density Models in Probabilistic Machine Learning Approaches for Data Analysis. ICAISC (2) (2019)
Thomas Villmann, Jensun Ravichandran, Andrea Villmann, David Nebel, Marika Kaden
Investigation of Activation Functions for Generalized Learning Vector Quantization. WSOM+ (2019)
Thomas Villmann, John Ravichandran, Andrea Villmann, David Nebel, Marika Kaden
Activation Functions for Generalized Learning Vector Quantization - A Performance Comparison. CoRR (2019)
Andrea Villmann, Marika Kaden, Sascha Saralajew, Thomas Villmann
Probabilistic Learning Vector Quantization with Cross-Entropy for Probabilistic Class Assignments in Classification Learning. ICAISC (1) (2018)
Andrea Villmann, Marika Kaden, Sascha Saralajew, Wieland Hermann, Thomas Villmann
Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach. ESANN (2018)
Thomas Villmann, Michael Biehl, Andrea Villmann, Sascha Saralajew
Fusion of deep learning architectures, multilayer feedforward networks and learning vector quantizers for deep classification learning. WSOM (2017)
Mohammad Mohammadi, Michael Biehl, Andrea Villmann, Thomas Villmann
Sequence Learning in Unsupervised and Supervised Vector Quantization Using Hankel Matrices. ICAISC (1) (2017)
David Nebel, Marika Kaden, Andrea Villmann, Thomas Villmann
Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning. Neurocomputing 268 (2017)