Journalartikel

• Quantum Computing Approaches for Vector Quantization— Current Perspectives and Developments.  Entropy. 540. 2023
• Quantum-Hybrid Neural Vector Quantization – A Mathematical Approach.  Artificial Intelligence and Soft Computing 2021. 246-257. 2021
• Quantum-inspired learning vector quantizers for prototype-based classification.  Neural Computing and Applications. 2020

Sammelbandbeitrag

• Quantum-inspired learning vector quantization for classification learning.  Proceedings of the 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'2020). 2020

Konferenzpaper

• Hyperbox-GLVQ Based on Min-Max-Neurons.  Lecture Notes in Networks and Systems. 22-31. 2024
• Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings.  Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS. 59-69. 2023
• Entwicklungsansatz eines datenbasierten Assistenzsystems zur dynamischen Ergonomiebewertung.  Scientific Reports 2023, Entwicklung hybrider Arbeitssysteme. 6-10. 2023
• Multilayer Perceptrons with Banach-Like Perceptrons Based on Semi-inner Products – About Approximation Completeness.  Artificial Intelligence and Soft Computing. 154-169. 2023
• Quantum-ready vector quantization: Prototype learning as a binary optimization problem.  ESANN 2023 Proceedings. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 257-262. 2023
• Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection.  ESANN 2023 Proceedings. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 65-70. 2023
• Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection.  ESANN 2023 Proceedings. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 65-70. 2023
• Steps Forward to Quantum Learning Vector Quantization for Classification Learning on a Theoretical Quantum Computer.  Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization. 63-73. 2022
• Quantum Computing for Efficient Learning in Prototype-based Vector Quantization.  Scientific Reports 2021, Ökologische Transformation in Technik, Wirtschaft und Gesellschaft?. 137-140. 2021

Konferenzposter