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Alexander Engelsberger

Observed name: A. Engelsberger
ORCID: 0000-0002-8547-2407
Observed ORCID: 0000-0002-8547-2407
OpenAlex ID: A5006936317
Quantum-inspired learning vector quantizers for prototype-based classification
2020 · Thomas Villmann, Alexander Engelsberger, et al. · Neural Computing and Applications · 17
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Quantum Computing Approaches for Vector Quantization—Current Perspectives and Developments
2023 · Alexander Engelsberger, Thomas Villmann · Entropy · 8
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Steps Forward to Quantum Learning Vector Quantization for Classification Learning on a Theoretical Quantum Computer
2022 · Alexander Engelsberger, Ronny Schubert, et al. · Lecture notes in networks and systems · 5
Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings
2023 · Katrin Bohnsack, Alexander Engelsberger, et al. · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · 4
Quantum-ready vector quantization: Prototype learning as a binary optimization problem
2023 · Alexander Engelsberger, Thomas Villmann · European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) · 4
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Quantum-Inspired Learning Vector Quantization for Classification Learning.
2020 · Thomas Villmann, Jensun Ravichandran, et al. · The European Symposium on Artificial Neural Networks · 3
Quantum-Hybrid Neural Vector Quantization – A Mathematical Approach
2021 · Thomas Villmann, Alexander Engelsberger · Lecture notes in computer science · 2
Mitigating the Bias in Data for Fairness Using an Advanced Generalized Learning Vector Quantization Approach -- FA(IR)$^2$MA-GLVQ
2025 · Marika Kaden, Alexander Engelsberger, et al. · European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) · 1
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Detecting Oncoming Vehicles at Night in Urban Scenarios - An Annotation Proof-Of-Concept
2024 · Lukas Ewecker, Niklas Wagner, et al. · IEEE Intelligent Vehicles Symposium · 1
Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection
2023 · Maximilian Münch, Katrin Sophie Bohnsack, et al. · European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) · 1
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FA(IR)2MA-GLVQ – A hidden-feature-bias mitigation approach for fairness in classification learning based on generalized matrix learning vector quantization
2026 · Marika Kaden, Ronny Schubert, et al. · Neurocomputing
Prototype-Based Classifiers and Vector Quantization on a Quantum Computer—Implementing Integer Arithmetic Oracles for Nearest Prototype Search
2026 · Alexander Engelsberger, Magdalena Pšeničkova, et al. · Entropy
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Diminishing Returns - Data Integer Quantization and its Effects on Training Dynamics of Distance Based Classifiers
2026 · Thomas Davies, Alexander Engelsberger, et al. · European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)
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Prototype Learning for Classification on Spherical Manifolds and Its Relation to Quantum Classification Approaches
2025 · Alexander Engelsberger, M. Psenickova, et al. · Lecture notes in computer science
Hyperbox-GLVQ Based on Min-Max-Neurons
2024 · Thomas Villmann, T. Davies, et al. · Lecture notes in networks and systems
Multilayer Perceptrons with Banach-Like Perceptrons Based on Semi-inner Products – About Approximation Completeness
2023 · Thomas Villmann, Alexander Engelsberger · Lecture notes in computer science
Works count: 16
Citation count: 46
H-index: 4
I10-index: 1
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