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)

How to Get the Most Out of U-Net for Glacier Calving Front Segmentation. - Maniraman Periyasamy; AmirAbbas Davari; Thorsten Seehaus; Matthias Braun 001; Andreas Maier 001; Vincent Christlein (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

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)

Batch Quantum Reinforcement Learning. - Maniraman Periyasamy; Marc Hölle; Marco Wiedmann; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (CoRR, 2023)

Cutting multi-control quantum gates with ZX calculus. - Christian Ufrecht; Maniraman Periyasamy; Sebastian Rietsch; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (Quantum, 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., 2023)

BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading. - Maniraman Periyasamy; Marc Hölle; Marco Wiedmann; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (IJCNN, 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)

Guided-SPSA: Simultaneous Perturbation Stochastic Approximation Assisted by the Parameter Shift Rule. - Maniraman Periyasamy; Axel Plinge; Christopher Mutschler; Daniel D. Scherer; Wolfgang Mauerer (QCE, 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 (QCE, 2024)

Fourier Analysis of Variational Quantum Circuits for Supervised Learning. - Marco Wiedmann; Maniraman Periyasamy; Daniel D. Scherer (CoRR, 2024)

Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks. - Alexander Mattick; Maniraman Periyasamy; Christian Ufrecht; Abhishek Y. Dubey; Christopher Mutschler; Axel Plinge; Daniel D. Scherer (CoRR, 2025)

CutReg: A loss regularizer for enhancing the scalability of QML via adaptive circuit cutting. - Maniraman Periyasamy; Christian Ufrecht; Daniel D. Scherer; Wolfgang Mauerer (CoRR, 2025)