Daniel D. Scherer

Orcid: 0000-0003-0355-4140

According to our database1, Daniel D. Scherer authored at least 20 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2020
2021
2022
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2024
2025
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Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Benchmarking Quantum Reinforcement Learning.
CoRR, January, 2025

2024
Fourier Analysis of Variational Quantum Circuits for Supervised Learning.
CoRR, 2024

Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization.
CoRR, 2024

SCIM MILQ: An HPC Quantum Scheduler.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Unitary Synthesis of Clifford+T Circuits with Reinforcement Learning.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Guided-SPSA: Simultaneous Perturbation Stochastic Approximation Assisted by the Parameter Shift Rule.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Comprehensive Library of Variational LSE Solvers.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Warm-Start Variational Quantum Policy Iteration.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
Uncovering instabilities in variational-quantum deep Q-networks.
J. Frankl. Inst., November, 2023

Cutting multi-control quantum gates with ZX calculus.
Quantum, October, 2023

Batch Quantum Reinforcement Learning.
CoRR, 2023

An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-Based Gradients.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Workshop Summary: Quantum Machine Learning.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Quantum Policy Gradient Algorithm with Optimized Action Decoding.
Proceedings of the International Conference on Machine Learning, 2023

2022
A Survey on Quantum Reinforcement Learning.
CoRR, 2022

Incremental Data-Uploading for Full-Quantum Classification.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

2020
High-Speed Collision Avoidance using Deep Reinforcement Learning and Domain Randomization for Autonomous Vehicles.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020


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