3 papers
quant-ph2025
AutoQML: A Framework for Automated Quantum Machine Learning
Marco Roth, David A. Kreplin, Daniel Basilewitsch +7
Automated Machine Learning (AutoML) has significantly advanced the efficiency of ML-focused software development by automating hyperparameter optimization and pipeline construction…
quant-ph2024
Application of quantum annealing for scalable robotic assembly line optimization: a case study
Moritz Willmann, Marcel Albus, Jan Schnabel +1
The even distribution and optimization of tasks across resources and workstations is a critical process in manufacturing aimed at maximizing efficiency, productivity, and profitabi…
quant-ph2023
sQUlearn -- A Python Library for Quantum Machine Learning
David A. Kreplin, Moritz Willmann, Jan Schnabel +3
sQUlearn introduces a user-friendly, NISQ-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine learning tools like scik…