Daniel D. Scherer

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 19

Top Topics

Discounted Reward

Policy Gradient

Quantum Computation

Reinforcement Learning

Top Venues

J. Frankl. Inst.

Publications

Nico Meyer, Martin Röhn, Jakob Murauer, Axel Plinge, Christopher Mutschler, Daniel D. Scherer
Comprehensive Library of Variational LSE Solvers. CoRR (2024)
Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Axel Plinge, Christopher Mutschler, Daniel D. Scherer, Andreas K. Maier
Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks. CoRR (2024)
Maniraman Periyasamy, Axel Plinge, Christopher Mutschler, Daniel D. Scherer, Wolfgang Mauerer
Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule. CoRR (2024)
Nico Meyer, Jakob Murauer, Alexander Popov, Christian Ufrecht, Axel Plinge, Christopher Mutschler, Daniel D. Scherer
Warm-Start Variational Quantum Policy Iteration. CoRR (2024)
Marco Wiedmann, Marc Hölle, Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-Based Gradients. QCE (2023)
Volker Tresp, Steffen Udluft, Daniel Hein, Werner Hauptmann, Martin Leib, Christopher Mutschler, Daniel D. Scherer, Wolfgang Mauerer
Workshop Summary: Quantum Machine Learning. QCE (2023)
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann
Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning. CoRR (2023)
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann
Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning. QCE (2023)
Christian Ufrecht, Maniraman Periyasamy, Sebastian Rietsch, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
Cutting multi-control quantum gates with ZX calculus. Quantum 7 (2023)
Maja Franz, Lucas Wolf, Maniraman Periyasamy, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Wolfgang Mauerer
Uncovering instabilities in variational-quantum deep Q-networks. J. Frankl. Inst. 360 (17) (2023)
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann
Quantum Policy Gradient Algorithm with Optimized Action Decoding. ICML (2023)
Maniraman Periyasamy, Marc Hölle, Marco Wiedmann, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
Batch Quantum Reinforcement Learning. CoRR (2023)
Marco Wiedmann, Marc Hölle, Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-based Gradients. CoRR (2023)
Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
A Survey on Quantum Reinforcement Learning. CoRR (2022)
Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
Incremental Data-Uploading for Full-Quantum Classification. CoRR (2022)
Maja Franz, Lucas Wolf, Maniraman Periyasamy, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Wolfgang Mauerer
Uncovering Instabilities in Variational-Quantum Deep Q-Networks. CoRR (2022)
Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
Incremental Data-Uploading for Full-Quantum Classification. QCE (2022)
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann
Quantum Policy Gradient Algorithm with Optimized Action Decoding. CoRR (2022)
Georgios D. Kontes, Daniel D. Scherer, Tim Nisslbeck, Janina Fischer, Christopher Mutschler
High-Speed Collision Avoidance using Deep Reinforcement Learning and Domain Randomization for Autonomous Vehicles. ITSC (2020)