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2020 – today
- 2025
[j5]Frederic Rapp
, David A. Kreplin, Marco F. Huber, Marco Roth:
Reinforcement learning-based architecture search for quantum machine learning. Mach. Learn. Sci. Technol. 6(1): 15041 (2025)- [j4]Jan Schnabel, Marco Roth:
Quantum kernel methods under scrutiny: a benchmarking study. Quantum Mach. Intell. 7(1): 58 (2025) - [j3]David A. Kreplin, Moritz Willmann, Jan Schnabel, Frederic Rapp, Manuel Hagelüken, Marco Roth:
sQUlearn: A Python Library for Quantum Machine Learning [Focus: Quantum Software and Its Engineering]. IEEE Softw. 42(5): 65-72 (2025) - [c1]Marco Roth, David A. Kreplin, Daniel Basilewitsch, João F. Bravo, Dennis Klau, Milan Marinov, Daniel Pranjic, Peter Schichtel, Horst Stühler, Moritz Willmann, Marc-André Zöller:
AutoQML: A Framework for Automated Quantum Machine Learning. QSW 2025: 81-91 - [i9]Marco Roth, David A. Kreplin, Daniel Basilewitsch, João F. Bravo, Dennis Klau, Milan Marinov, Daniel Pranjic, Horst Stühler, Moritz Willmann, Marc-André Zöller:
AutoQML: A Framework for Automated Quantum Machine Learning. CoRR abs/2502.21025 (2025) - [i8]Roberto Flórez Ablan, Marco Roth, Jan Schnabel:
On the similarity of bandwidth-tuned quantum kernels and classical kernels. CoRR abs/2503.05602 (2025) - 2024
- [j2]Frederic Rapp, Marco Roth:
Quantum Gaussian process regression for Bayesian optimization. Quantum Mach. Intell. 6(1): 5 (2024) - [j1]David A. Kreplin, Marco Roth:
Reduction of finite sampling noise in quantum neural networks. Quantum 8: 1385 (2024) - [i7]Frederic Rapp, David A. Kreplin, Marco F. Huber, Marco Roth:
Reinforcement learning-based architecture search for quantum machine learning. CoRR abs/2406.02717 (2024) - [i6]Jan Schnabel, Marco Roth:
Quantum Kernel Methods under Scrutiny: A Benchmarking Study. CoRR abs/2409.04406 (2024) - [i5]Manuel Hagelüken, Marco F. Huber, Marco Roth:
Data Efficient Prediction of excited-state properties using Quantum Neural Networks. CoRR abs/2412.09423 (2024) - 2023
- [i4]Frederic Rapp, Marco Roth:
Quantum Gaussian Process Regression for Bayesian Optimization. CoRR abs/2304.12923 (2023) - [i3]David Kreplin, Marco Roth:
Reduction of finite sampling noise in quantum neural networks. CoRR abs/2306.01639 (2023) - [i2]David A. Kreplin, Moritz Willmann, Jan Schnabel, Frederic Rapp, Marco Roth:
sQUlearn - A Python Library for Quantum Machine Learning. CoRR abs/2311.08990 (2023) - 2022
- [i1]Paul-Amaury Matt, Rosina Ziegler, Danilo Brajovic, Marco Roth, Marco F. Huber:
A Nested Genetic Algorithm for Explaining Classification Data Sets with Decision Rules. CoRR abs/2209.07575 (2022)
2010 – 2019
- 2019
- [b1]Marco Roth:
Analysis of scalable coupling schemes for superconducting quantum computers. RWTH Aachen University, Germany, 2019, pp. 1-125
Coauthor Index
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