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Quantum-enhanced machine learning

arXiv 1610.08251 ↗First posted 26 Oct 2016quant-ph cs.AI cs.LGcited by 79

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Abstract (arXiv)

The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention. Within our approach, we tackle the problem of quantum enhancements in reinforcement learning as well, and propose a systematic scheme for providing improvements. As an example, we show that quadratic improvements in learning efficiency, and exponential improvements in performance over limited time periods, can be obtained for a broad class of learning problems.

Key facts. Cited by 79 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Oct 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 14; 2022: 11; 2023: 14; 2024: 10; 2025: 21; 2026: 9.

79 papers.

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  1. 2021Parametrized quantum policies for reinforcement learningcited by 87
  2. 2022A Survey on Quantum Reinforcement Learningcited by 50
  3. 2022Experimental quantum adversarial learning with programmable superconducting qubitscited by 38
  4. 2021Recent advances for quantum classifierscited by 35
  5. 2021QTN-VQC: An End-to-End Learning framework for Quantum Neural Networkscited by 27
  6. 2021Quantum Algorithms for Reinforcement Learning with a Generative Modelcited by 24
  7. 2021Universal Adversarial Examples and Perturbations for Quantum Classifierscited by 22
  8. 2022Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learningcited by 21
  9. 2022Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regretscited by 19
  10. 2021Deep Reinforcement Learning with Quantum-inspired Experience Replaycited by 18
  11. 2023Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learningcited by 17
  12. 2021Hybrid quantum convolutional neural networks model for COVID-19 prediction using chest X-Ray imagescited by 16
38 more
  1. 2022Multiclass classification using quantum convolutional neural networks with hybrid quantum-classical learningcited by 16
  2. 2022Policy Gradients using Variational Quantum Circuitscited by 15
  3. 2022Quantum policy gradient algorithmscited by 15
  4. 2023Detecting Clouds in Multispectral Satellite Images Using Quantum-Kernel Support Vector Machinescited by 15
  5. 2022Quantum Deep Reinforcement Learning for Robot Navigation Taskscited by 14
  6. 2025Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networkscited by 10
  7. 2023Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regretcited by 9
  8. 2025Benchmarking Quantum Reinforcement Learningcited by 9
  9. 2025A Primer on Quantum Machine Learningcited by 9
  10. 2022Experimental quantum pattern recognition in IBMQ and diamond NVscited by 8
  11. 2021Quantum Embedding Search for Quantum Machine Learningcited by 7
  12. 2023Expressibility-induced Concentration of Quantum Neural Tangent Kernelscited by 7
  13. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generationcited by 7
  14. 2021Quantum adaptive agents with efficient long-term memoriescited by 6
  15. 2023Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learningcited by 6
  16. 2023Application of quantum-inspired generative models to small molecular datasetscited by 5
  17. 2024Entanglement-induced provable and robust quantum learning advantagescited by 4
  18. 2022QuAnt: Quantum Annealing with Learnt Couplingscited by 3
  19. 2023Machine-learning based noise characterization and correction on neutral atoms NISQ devicescited by 3
  20. 2023Toward Automated Quantum Variational Machine Learningcited by 3
  21. 2024Quantum-Classical Separations in Shallow-Circuit-Based Learning with and without Noisescited by 3
  22. 2024KACQ-DCNN: Uncertainty-Aware Interpretable Kolmogorov-Arnold Classical-Quantum Dual-Channel Neural Network for Heart Disease Detectioncited by 3
  23. 2024Quantum framework for Reinforcement Learning: Integrating Markov decision process, quantum arithmetic, and trajectory searchcited by 3
  24. 2025Distributed Quantum Neural Networks on Distributed Photonic Quantum Computingcited by 3
  25. 2021On the effects of biased quantum random numbers on the initialization of artificial neural networkscited by 2
  26. 2021Discriminating Quantum States with Quantum Machine Learningcited by 2
  27. 2021From Digital Humanities to Quantum Humanities: Potentials and Applicationscited by 1
  28. 2021Image Compression and Classification Using Qubits and Quantum Deep Learningcited by 1
  29. 2022Predict better with less training data using a QNNcited by 1
  30. 2023Learning Quantum Processes with Memory -- Quantum Recurrent Neural Networkscited by 1
  31. 2023Quantum Text Classifier -- A Synchronistic Approach Towards Classical and Quantum Machine Learningcited by 1
  32. 2024TriQXNet: Forecasting Dst Index from Solar Wind Data Using an Interpretable Parallel Classical-Quantum Framework with Uncertainty Quantificationcited by 1
  33. 2025Comparative Analysis of Quantum and Classical Support Vector Classifiers for Software Bug Prediction: An Exploratory Studycited by 1
  34. 2025Quantum-Inspired Reinforcement Learning in the Presence of Epistemic Ambivalencecited by 1
  35. 2025A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methodscited by 1
  36. 2025Advances in Machine Learning: Where Can Quantum Techniques Help?cited by 1
  37. 2025Quantum-Enhanced Forecasting for Deep Reinforcement Learning in Algorithmic Tradingcited by 1
  38. 2025Quantum Deep Learning Still Needs a Quantum Leapcited by 1

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