Incremental Data-Uploading for Full-Quantum Classification. - Maniraman Periyasamy; Nico Meyer; Christian Ufrecht; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (QCE, 2022)

A Survey on Quantum Reinforcement Learning. - Nico Meyer; Christian Ufrecht; Maniraman Periyasamy; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (CoRR, 2022)

Quantum Policy Gradient Algorithm with Optimized Action Decoding. - Nico Meyer; Daniel D. Scherer; Axel Plinge; Christopher Mutschler; Michael J. Hartmann (ICML, 2023)

Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning. - Nico Meyer; Daniel D. Scherer; Axel Plinge; Christopher Mutschler; Michael J. Hartmann (QCE, 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 (QCE, 2023)

Warm-Start Variational Quantum Policy Iteration. - Nico Meyer; Jakob Murauer; Alexander Popov; Christian Ufrecht; Axel Plinge; Christopher Mutschler; Daniel D. Scherer (QCE, 2024)

Comprehensive Library of Variational LSE Solvers. - Nico Meyer; Martin Röhn; Jakob Murauer; Axel Plinge; Christopher Mutschler; Daniel D. Scherer (QCE, 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 001 (QCE, 2024)

Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization. - Nico Meyer; Julian Berberich; Christopher Mutschler; Daniel D. Scherer (CoRR, 2024)

Benchmarking Quantum Reinforcement Learning. - Nico Meyer; Christian Ufrecht; George Yammine; Georgios D. Kontes; Christopher Mutschler; Daniel D. Scherer (CoRR, 2025)

Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction. - Nico Meyer; Christopher Mutschler; Andreas K. Maier; Daniel D. Scherer (CoRR, 2025)