A Survey on Quantum Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Meyer, Nico, Ufrecht, Christian, Periyasamy, Maniraman, Scherer, Daniel D., Plinge, Axel, Mutschler, Christopher |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Incremental Data-Uploading for Full-Quantum Classification
by: Periyasamy, Maniraman, et al.
Published: (2022)
by: Periyasamy, Maniraman, et al.
Published: (2022)
Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks
by: Meyer, Nico, et al.
Published: (2024)
by: Meyer, Nico, et al.
Published: (2024)
An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-based Gradients
by: Wiedmann, Marco, et al.
Published: (2023)
by: Wiedmann, Marco, et al.
Published: (2023)
Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks
by: Mattick, Alexander, et al.
Published: (2025)
by: Mattick, Alexander, et al.
Published: (2025)
BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading
by: Periyasamy, Maniraman, et al.
Published: (2023)
by: Periyasamy, Maniraman, et al.
Published: (2023)
Warm-Start Variational Quantum Policy Iteration
by: Meyer, Nico, et al.
Published: (2024)
by: Meyer, Nico, et al.
Published: (2024)
Unitary Synthesis of Clifford+T Circuits with Reinforcement Learning
by: Rietsch, Sebastian, et al.
Published: (2024)
by: Rietsch, Sebastian, et al.
Published: (2024)
Benchmarking Quantum Reinforcement Learning
by: Meyer, Nico, et al.
Published: (2025)
by: Meyer, Nico, et al.
Published: (2025)
CutReg: A loss regularizer for enhancing the scalability of QML via adaptive circuit cutting
by: Periyasamy, Maniraman, et al.
Published: (2025)
by: Periyasamy, Maniraman, et al.
Published: (2025)
Optimal joint cutting of two-qubit rotation gates
by: Ufrecht, Christian, et al.
Published: (2023)
by: Ufrecht, Christian, et al.
Published: (2023)
Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule
by: Periyasamy, Maniraman, et al.
Published: (2024)
by: Periyasamy, Maniraman, et al.
Published: (2024)
Fourier Analysis of Variational Quantum Circuits for Supervised Learning
by: Wiedmann, Marco, et al.
Published: (2024)
by: Wiedmann, Marco, et al.
Published: (2024)
Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization
by: Meyer, Nico, et al.
Published: (2024)
by: Meyer, Nico, et al.
Published: (2024)
Comprehensive Library of Variational LSE Solvers
by: Meyer, Nico, et al.
Published: (2024)
by: Meyer, Nico, et al.
Published: (2024)
Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction
by: Meyer, Nico, et al.
Published: (2025)
by: Meyer, Nico, et al.
Published: (2025)
Learning to Concatenate Quantum Codes
by: Meyer, Nico, et al.
Published: (2026)
by: Meyer, Nico, et al.
Published: (2026)
Learning Logical Operations for Arbitrary Quantum Error Correction Codes
by: Meyer, Nico, et al.
Published: (2026)
by: Meyer, Nico, et al.
Published: (2026)
Improving Quantum and Classical Decomposition Methods for Vehicle Routing
by: Herzog, Laura S., et al.
Published: (2024)
by: Herzog, Laura S., et al.
Published: (2024)
SCIM MILQ: An HPC Quantum Scheduler
by: Seitz, Philipp, et al.
Published: (2024)
by: Seitz, Philipp, et al.
Published: (2024)
Shot-Based Quantum Encoding: A Data-Loading Paradigm for Quantum Neural Networks
by: Kyriacou, Basil, et al.
Published: (2026)
by: Kyriacou, Basil, et al.
Published: (2026)
Soft-Quantum Algorithms
by: Kyriacou, Basil, et al.
Published: (2026)
by: Kyriacou, Basil, et al.
Published: (2026)
Quantum Wasserstein Compilation: Unitary Compilation using the Quantum Earth Mover's Distance
by: Richter, Marvin, et al.
Published: (2024)
by: Richter, Marvin, et al.
Published: (2024)
Superposed parameterised quantum circuits
by: Patapovich, Viktoria, et al.
Published: (2025)
by: Patapovich, Viktoria, et al.
Published: (2025)
C-MCTS: Safe Planning with Monte Carlo Tree Search
by: Parthasarathy, Dinesh, et al.
Published: (2023)
by: Parthasarathy, Dinesh, et al.
Published: (2023)
A Transferable Machine Learning Approach to Predict Optimized Orbitals for Electronic Structure Problems
by: van der Horst, Lucas, et al.
Published: (2026)
by: van der Horst, Lucas, et al.
Published: (2026)
Joint Cutting for Hybrid Schrödinger-Feynman Simulation of Quantum Circuits
by: Herzog, Laura S., et al.
Published: (2025)
by: Herzog, Laura S., et al.
Published: (2025)
Optimized Circuit Cutting for QAOA Sampling Tasks
by: Wagner, Friedrich, et al.
Published: (2025)
by: Wagner, Friedrich, et al.
Published: (2025)
Beyond Reinforcement Learning: Fast and Scalable Quantum Circuit Synthesis
by: Theißinger, Lukas, et al.
Published: (2026)
by: Theißinger, Lukas, et al.
Published: (2026)
On Quantum Circuits for Discrete Graphical Models
by: Piatkowski, Nico, et al.
Published: (2022)
by: Piatkowski, Nico, et al.
Published: (2022)
Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passes
by: Mills, Daniel, et al.
Published: (2026)
by: Mills, Daniel, et al.
Published: (2026)
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning
by: Heese, Raoul, et al.
Published: (2023)
by: Heese, Raoul, et al.
Published: (2023)
Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
by: Lee, Yu-Ting, et al.
Published: (2026)
by: Lee, Yu-Ting, et al.
Published: (2026)
Reinforcement Learning for Variational Quantum Circuits Design
by: Foderà, Simone, et al.
Published: (2024)
by: Foderà, Simone, et al.
Published: (2024)
Minor Embedding for Quantum Annealing with Reinforcement Learning
by: Nembrini, Riccardo, et al.
Published: (2025)
by: Nembrini, Riccardo, et al.
Published: (2025)
Challenges for Reinforcement Learning in Quantum Circuit Design
by: Altmann, Philipp, et al.
Published: (2023)
by: Altmann, Philipp, et al.
Published: (2023)
Reinforcement Learning for Node Selection in Branch-and-Bound
by: Mattick, Alexander, et al.
Published: (2023)
by: Mattick, Alexander, et al.
Published: (2023)
Model-based Offline Quantum Reinforcement Learning
by: Eisenmann, Simon, et al.
Published: (2024)
by: Eisenmann, Simon, et al.
Published: (2024)
Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study
by: Stenzel, Gerhard, et al.
Published: (2026)
by: Stenzel, Gerhard, et al.
Published: (2026)
A Strategy for Preparing Quantum Squeezed States Using Reinforcement Learning
by: Zhao, X. L., et al.
Published: (2024)
by: Zhao, X. L., et al.
Published: (2024)
Dissecting Quantum Reinforcement Learning: A Systematic Evaluation of Key Components
by: Lazaro, Javier, et al.
Published: (2025)
by: Lazaro, Javier, et al.
Published: (2025)
Similar Items
-
Incremental Data-Uploading for Full-Quantum Classification
by: Periyasamy, Maniraman, et al.
Published: (2022) -
Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks
by: Meyer, Nico, et al.
Published: (2024) -
An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-based Gradients
by: Wiedmann, Marco, et al.
Published: (2023) -
Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks
by: Mattick, Alexander, et al.
Published: (2025) -
BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading
by: Periyasamy, Maniraman, et al.
Published: (2023)