Nico Meyer

19 papers A* 2Misc 6Journal 11
YearRankTypeTitle / Venue / Authors
2025 A* conf
Benchmarking Quantum Reinforcement Learning.
ICML
Nico Meyer, Christian Ufrecht, George Yammine, Georgios D. Kontes, Christopher Mutschler, Daniel D. Scherer
2025 J jnl
Benchmarking Quantum Reinforcement Learning.
CoRR
Nico Meyer, Christian Ufrecht, George Yammine, Georgios D. Kontes, Christopher Mutschler, Daniel D. Scherer
2025 J jnl
Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction.
CoRR
Nico Meyer, Christopher Mutschler, Andreas K. Maier, Daniel D. Scherer
2024 Misc conf
Comprehensive Library of Variational LSE Solvers.
QCE
Nico Meyer, Martin Röhn, Jakob Murauer, Axel Plinge, Christopher Mutschler, Daniel D. Scherer
2024 J jnl
Comprehensive Library of Variational LSE Solvers.
CoRR
Nico Meyer, Martin Röhn, Jakob Murauer, Axel Plinge, Christopher Mutschler, Daniel D. Scherer
2024 Misc conf
Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks.
QCE
Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Axel Plinge, Christopher Mutschler, Daniel D. Scherer, Andreas Maier
2024 J jnl
Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks.
CoRR
Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Axel Plinge, Christopher Mutschler, Daniel D. Scherer, Andreas K. Maier
2024 J jnl
Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization.
CoRR
Nico Meyer, Julian Berberich, Christopher Mutschler, Daniel D. Scherer
2024 Misc conf
Warm-Start Variational Quantum Policy Iteration.
QCE
Nico Meyer, Jakob Murauer, Alexander Popov, Christian Ufrecht, Axel Plinge, Christopher Mutschler, Daniel D. Scherer
2024 J jnl
Warm-Start Variational Quantum Policy Iteration.
CoRR
Nico Meyer, Jakob Murauer, Alexander Popov, Christian Ufrecht, Axel Plinge, Christopher Mutschler, Daniel D. Scherer
2023 Misc conf
An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-Based Gradients.
QCE
Marco Wiedmann, Marc Hölle, Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
2023 J jnl
An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-based Gradients.
CoRR
Marco Wiedmann, Marc Hölle, Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
2023 Misc conf
Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning.
QCE
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann
2023 J jnl
Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning.
CoRR
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann
2023 A* conf
Quantum Policy Gradient Algorithm with Optimized Action Decoding.
ICML
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann
2022 J jnl
A Survey on Quantum Reinforcement Learning.
CoRR
Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
2022 Misc conf
Incremental Data-Uploading for Full-Quantum Classification.
QCE
Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
2022 J jnl
Incremental Data-Uploading for Full-Quantum Classification.
CoRR
Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler
2022 J jnl
Quantum Policy Gradient Algorithm with Optimized Action Decoding.
CoRR
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, Michael J. Hartmann