Maniraman Periyasamy

According to our database, Maniraman Periyasamy authored at least 14 papers between 2022 and 2025.

Collaborative distances:

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

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, June, 2025

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, April, 2025

2024

Fourier Analysis of Variational Quantum Circuits for Supervised Learning.

Marco Wiedmann, Maniraman Periyasamy, Daniel D. Scherer

CoRR, 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

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

2022

How to Get the Most Out of U-Net for Glacier Calving Front Segmentation.

Maniraman Periyasamy, AmirAbbas Davari, Thorsten Seehaus, Matthias Braun, Andreas Maier, Vincent Christlein

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 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