Daniel D. Scherer

According to our database, Daniel D. Scherer authored at least 20 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Benchmarking Quantum Reinforcement Learning.

Nico Meyer, Christian Ufrecht, George Yammine, Georgios D. Kontes, Christopher Mutschler, Daniel D. Scherer

CoRR, January, 2025

2024

Fourier Analysis of Variational Quantum Circuits for Supervised Learning.

Marco Wiedmann, Maniraman Periyasamy, Daniel D. Scherer

CoRR, 2024

Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization.

Nico Meyer, Julian Berberich, Christopher Mutschler, Daniel D. Scherer

CoRR, 2024

SCIM MILQ: An HPC Quantum Scheduler.

Philipp Seitz, Manuel Geiger, Christian Ufrecht, Axel Plinge, Christopher Mutschler, Daniel D. Scherer, Christian B. Mendl

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Unitary Synthesis of Clifford+T Circuits with Reinforcement Learning.

Sebastian Rietsch, Abhishek Y. Dubey, Christian Ufrecht, Maniraman Periyasamy, Axel Plinge, Christopher Mutschler, Daniel D. Scherer

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Guided-SPSA: Simultaneous Perturbation Stochastic Approximation Assisted by the Parameter Shift Rule.

Maniraman Periyasamy, Axel Plinge, Christopher Mutschler, Daniel D. Scherer, Wolfgang Mauerer

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks.

Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Axel Plinge, Christopher Mutschler, Daniel D. Scherer, Andreas Maier

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Comprehensive Library of Variational LSE Solvers.

Nico Meyer, Martin Röhn, Jakob Murauer, Axel Plinge, Christopher Mutschler, Daniel D. Scherer

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Warm-Start Variational Quantum Policy Iteration.

Nico Meyer, Jakob Murauer, Alexander Popov, Christian Ufrecht, Axel Plinge, Christopher Mutschler, Daniel D. Scherer

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading.

Maniraman Periyasamy, Marc Hölle, Marco Wiedmann, Daniel D. Scherer, Axel Plinge, Christopher Mutschler

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Uncovering instabilities in variational-quantum deep Q-networks.

Maja Franz, Lucas Wolf, Maniraman Periyasamy, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Wolfgang Mauerer

J. Frankl. Inst., November, 2023

Cutting multi-control quantum gates with ZX calculus.

Christian Ufrecht, Maniraman Periyasamy, Sebastian Rietsch, Daniel D. Scherer, Axel Plinge, Christopher Mutschler

Quantum, October, 2023

Batch Quantum Reinforcement Learning.

Maniraman Periyasamy, Marc Hölle, Marco Wiedmann, Daniel D. Scherer, Axel Plinge, Christopher Mutschler

CoRR, 2023

An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-Based Gradients.

Marco Wiedmann, Marc Hölle, Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Workshop Summary: Quantum Machine Learning.

Volker Tresp, Steffen Udluft, Daniel Hein, Werner Hauptmann, Martin Leib, Christopher Mutschler, Daniel D. Scherer, Wolfgang Mauerer

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning.

Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Quantum Policy Gradient Algorithm with Optimized Action Decoding.

Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann

Proceedings of the International Conference on Machine Learning, 2023

2022

A Survey on Quantum Reinforcement Learning.

Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Daniel D. Scherer, Axel Plinge, Christopher Mutschler

CoRR, 2022

Incremental Data-Uploading for Full-Quantum Classification.

Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

2020

High-Speed Collision Avoidance using Deep Reinforcement Learning and Domain Randomization for Autonomous Vehicles.

Georgios D. Kontes, Daniel D. Scherer, Tim Nisslbeck, Janina Fischer, Christopher Mutschler

Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020