Alexander Engelsberger

13 papers B 3C 1Journal 4Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FA(IR)2MA-GLVQ - A hidden-feature-bias mitigation approach for fairness in classification learning based on generalized matrix learning vector quantization. Neurocomputing Marika Kaden, Ronny Schubert, Julius Voigt, Lynn V. Reuss, Alexander Engelsberger, Sofie Lövdal, Elina L. van den Brandhof, Michael Biehl, Thomas Villmann
2026	J	`jnl`	Prototype-Based Classifiers and Vector Quantization on a Quantum Computer - Implementing Integer Arithmetic Oracles for Nearest Prototype Search. Entropy Alexander Engelsberger, M. Psenickova, Thomas Villmann
2025	—	`conf`	Prototype Learning for Classification on Spherical Manifolds and Its Relation to Quantum Classification Approaches. ICAISC (1) Alexander Engelsberger, M. Psenickova, Thomas Villmann
2024	C	`conf`	Detecting Oncoming Vehicles at Night in Urban Scenarios - An Annotation Proof-Of-Concept. IV Lukas Ewecker, Niklas Wagner, Tim Brühl, Robin Schwager, Tin Stribor Sohn, Alexander Engelsberger, Jensun Ravichandran, Hanno Stage, Jacob Langner, Sascha Saralajew
2024	—	`conf`	Hyperbox-GLVQ Based on Min-Max-Neurons. WSOM+ Thomas Villmann, T. Davies, Alexander Engelsberger
2023	—	`conf`	Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings. BIOINFORMATICS Katrin Sophie Bohnsack, Alexander Engelsberger, Marika Kaden, Thomas Villmann
2023	J	`jnl`	Quantum Computing Approaches for Vector Quantization - Current Perspectives and Developments. Entropy Alexander Engelsberger, Thomas Villmann
2023	B	`conf`	Quantum-ready vector quantization: Prototype learning as a binary optimization problem. ESANN Alexander Engelsberger, Thomas Villmann
2023	B	`conf`	Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection. ESANN Maximilian Münch, Katrin Sophie Bohnsack, Alexander Engelsberger, Frank-Michael Schleif, Thomas Villmann
2022	—	`conf`	Multilayer Perceptrons with Banach-Like Perceptrons Based on Semi-inner Products - About Approximation Completeness. ICAISC (1) Thomas Villmann, Alexander Engelsberger
2022	J	`jnl`	Quantum-inspired learning vector quantizers for prototype-based classification. Neural Comput. Appl. Thomas Villmann, Alexander Engelsberger, Jensun Ravichandran, Andrea Villmann, Marika Kaden
2021	—	`conf`	Quantum-Hybrid Neural Vector Quantization - A Mathematical Approach. ICAISC (1) Thomas Villmann, Alexander Engelsberger
2020	B	`conf`	Quantum-Inspired Learning Vector Quantization for Classification Learning. ESANN Thomas Villmann, Jensun Ravichandran, Alexander Engelsberger, Andrea Villmann, Marika Kaden