Alexander Engelsberger

According to our database, Alexander Engelsberger authored at least 15 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

FA(IR)2MA-GLVQ - A hidden-feature-bias mitigation approach for fairness in classification learning based on generalized matrix learning vector quantization.

Marika Kaden, Ronny Schubert, Julius Voigt, Lynn V. Reuss, Alexander Engelsberger, Sofie Lövdal, Elina L. van den Brandhof, Michael Biehl, Thomas Villmann

Neurocomputing, 2026

Prototype-Based Classifiers and Vector Quantization on a Quantum Computer - Implementing Integer Arithmetic Oracles for Nearest Prototype Search.

Alexander Engelsberger, Magdalena Psenickova, Thomas Villmann

Entropy, 2026

Diminishing Returns - Data Integer Quantization and its Effects on Training Dynamics of Distance Based Classifiers.

Thomas Davies, Alexander Engelsberger, Magdalena Psenickova, Thomas Villmann

Proceedings of the 34th European Symposium on Artificial Neural Networks, 2026

2025

Prototype Learning for Classification on Spherical Manifolds and Its Relation to Quantum Classification Approaches.

Alexander Engelsberger, Magdalena Psenickova, Thomas Villmann

Proceedings of the Artificial Intelligence and Soft Computing, 2025

Mitigating the Bias in Data for Fairness Using an Advanced Generalized Learning Vector Quantization Approach - FA(IR)$^2$MA-GLVQ.

Marika Kaden, Alexander Engelsberger, Ronny Schubert, Sofie Lövdal, Elina L. van den Brandhof, Michael Biehl, Thomas Villmann

Proceedings of the 33rd European Symposium on Artificial Neural Networks, 2025

2024

Hyperbox-GLVQ Based on Min-Max-Neurons.

Thomas Villmann, Thomas Davies, Alexander Engelsberger

Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond, 2024

Detecting Oncoming Vehicles at Night in Urban Scenarios - An Annotation Proof-Of-Concept.

Lukas Ewecker, Niklas Wagner, Tim Brühl, Robin Schwager, Tin Stribor Sohn, Alexander Engelsberger, Jensun Ravichandran, Hanno Stage, Jacob Langner, Sascha Saralajew

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

2023

Quantum Computing Approaches for Vector Quantization - Current Perspectives and Developments.

Alexander Engelsberger, Thomas Villmann

Entropy, March, 2023

Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection.

Maximilian Münch, Katrin Sophie Bohnsack, Alexander Engelsberger, Frank-Michael Schleif, Thomas Villmann

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Quantum-ready vector quantization: Prototype learning as a binary optimization problem.

Alexander Engelsberger, Thomas Villmann

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings.

Katrin Sophie Bohnsack, Alexander Engelsberger, Marika Kaden, Thomas Villmann

Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023

2022

Quantum-inspired learning vector quantizers for prototype-based classification.

Thomas Villmann, Alexander Engelsberger, Jensun Ravichandran, Andrea Villmann, Marika Kaden

Neural Comput. Appl., 2022

Multilayer Perceptrons with Banach-Like Perceptrons Based on Semi-inner Products - About Approximation Completeness.

Thomas Villmann, Alexander Engelsberger

Proceedings of the Artificial Intelligence and Soft Computing, 2022

2021

Quantum-Hybrid Neural Vector Quantization - A Mathematical Approach.

Thomas Villmann, Alexander Engelsberger

Proceedings of the Artificial Intelligence and Soft Computing, 2021

2020

Quantum-Inspired Learning Vector Quantization for Classification Learning.

Thomas Villmann, Jensun Ravichandran, Alexander Engelsberger, Andrea Villmann, Marika Kaden

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020