43 citations · 64 across the 10 of their papers we have counts for
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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-ph2024★ 43 cited
Quantum Kernel Methods under Scrutiny: A Benchmarking Study
Jan Schnabel, Marco Roth
Since the entry of kernel theory in the field of quantum machine learning, quantum kernel methods (QKMs) have gained increasing attention with regard to both probing promising appl…
quant-ph2024★ 12 cited
Reinforcement learning-based architecture search for quantum machine learning
Frederic Rapp, David A. Kreplin, Marco F. Huber +1
Quantum machine learning models use encoding circuits to map data into a quantum Hilbert space. While it is well known that the architecture of these circuits significantly influen…