Meyer, Nico; Ufrecht, Christian; Yammine, George; Kontes, Georgios; Mutschler, Christopher; Scherer, Daniel D. (2025):
Benchmarking Quantum Reinforcement Learning
in: 2025 arXiv.org, pp. 1-29.
Richter, Martin; Dubey, Abhishek Y.; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D.; Hartmann, Michael J. (2025):
Quantum Wasserstein Compilation: Unitary Compilation using the Quantum Earth Mover's Distance
in: 2025 arXiv.org, pp. 1-13.
Wiedmann, Marco; Periyasamy, Maniraman; Scherer, Daniel D. (2024):
Fourier Analysis of Variational Quantum Circuits for Supervised Learning
in: 2024 arXiv.org, pp. 1-12.
Meyer, Nico; Berberich, Julian; Mutschler, Christopher; Scherer, Daniel D. (2024):
Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization
in: 2024 arXiv.org, pp. 1-10.
Rietsch, Sebastian; Dubey, Abishek Y.; Ufrecht, Christian; Periyasamy, Maniraman; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D. (2024):
Unitary Synthesis of Clifford+T Circuits with Reinforcement Learning
in: 2024 arXiv.org, pp. 1-12.
Meyer, Nico; Röhn, Martin; Murauer, Jakob; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D. (2024):
Comprehensive Library of Variational LSE Solvers
in: 2024 2nd International Workshop on Quantum Machine Learning: From Research to Practice (QML@QCE 2024), pp. 1-4.
Meyer, Nico; Murauer, Jakob; Popov, Alexander; Ufrecht, Christian; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D. (2024):
Warm-Start Variational Quantum Policy Iteration
in: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), pp. 1-9.
Meyer, Nico; Ufrecht, Christian; Periyasamy, Maniraman; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D.; Maier, Andreas (2024):
Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks,
in: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), pp. 1-7.
Ufrecht, Christian; Herzog, Laura S.; Scherer, Daniel D.; Periyasamy, Maniraman; Rietsch, Sebastian; Plinge, Axel; Mutschler, Christopher (2024):
Optimal joint cutting of two-qubit rotation gates
in: 2024 arXiv.org, pp. 1-9.
Periyasamy, Maniraman; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D.; Mauerer, Wolfgang (2024):
Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule
in: 2024 arXiv.org, pp. 1-12.
Herzog, Laura S.; Wagner, Friedrich; Ufrecht, Christian; Palackal, Lilly; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D. (2024):
Improving Quantum and Classical Decomposition Methods for Vehicle Routing
in: 2024 arXiv.org, pp. 1-10.
Seitz, Philipp; Geiger, Manuel; Ufrecht, Christian; Plinge, Axel; Mutschler, Christopher; Scherer, Daniel D.; Mendl, Christian B. (2024):
SCIM MILQ: An HPC Quantum Scheduler
in: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), pp. 292-298.
Periyasamy, Maniraman; Hölle, Marc; Wiedmann, Marco; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher (2024):
BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading
in: 2024 International Joint Conference on Neural Networks (IJCNN), pp. 1-9.
Meyer, Nico; Ufrecht, Christian; Periyasamy, Maniraman; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher (2024):
A Survey on Quantum Reinforcement Learning
in: 2024 arXiv.org, pp. 1-83.
Ufrecht, Christian; Periyasamy, Maniraman; Rietsch, Sebastian; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher (2023):
Cutting multi-control quantum gates with ZX calculus
in: 2023 Quantum, Volume 7, pp. 1147-1160.
Meyer, Nico; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher; Hartmann, Michael J. (2023):
Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning
in: 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), pp. 36-41.
Meyer, Nico; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher; Hartmann, Michael J. (2023):
Quantum Policy Gradient Algorithm with Optimized Action Decoding,
in: 2023 Proceedings of the 40th International Conference on Machine Learning (ICML), pp. 1-22.
Wiedmann, Marco; Hölle, Marc; Periyasamy, Maniraman; Meyer, Nico; Ufrecht, Christian; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher (2023):
An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-based Gradients
in: 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), pp. 450-456.
Franz, Maja; Wolf, Lucas; Periyasamy, Maniraman; Ufrecht, Christian; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher; Mauerer, Wolfgang (2022):
Uncovering instabilities in variational-quantum deep Q-networks,
in: 2022 Journal of the Franklin Institute, Volume 360, Issue 17, pp. 13822-13844.
Periyasamy, Maniraman; Meyer, Nico; Ufrecht, Christian; Scherer, Daniel D.; Plinge, Axel; Mutschler, Christopher (2022):
Incremental Data-Uploading for Full-Quantum Classification
in: 2022 IEEE International Conference on Quantum Computing and Engineering (QCE), pp. 31-37.