mlsanityData to 14 Oct 2026

Quantum generative adversarial networks

arXiv 1804.08641 ↗First posted 23 Apr 2018quant-ph cs.LGcited by 128

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Abstract (arXiv)

Quantum machine learning is expected to be one of the first potential general-purpose applications of near-term quantum devices. A major recent breakthrough in classical machine learning is the notion of generative adversarial training, where the gradients of a discriminator model are used to train a separate generative model. In this work and a companion paper, we extend adversarial training to the quantum domain and show how to construct generative adversarial networks using quantum circuits. Furthermore, we also show how to compute gradients -- a key element in generative adversarial network training -- using another quantum circuit. We give an example of a simple practical circuit ansatz to parametrize quantum machine learning models and perform a simple numerical experiment to demonstrate that quantum generative adversarial networks can be trained successfully.

Key facts. Cited by 128 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Apr 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 24; 2022: 20; 2023: 20; 2024: 19; 2025: 26; 2026: 19.

128 papers.

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  1. 2021Generalization in quantum machine learning from few training datacited by 216
  2. 2023Challenges and Opportunities in Quantum Machine Learningcited by 203
  3. 2021Federated Quantum Machine Learningcited by 82
  4. 2021Reinforcement learning for optimization of variational quantum circuit architecturescited by 77
  5. 2022Theory for Equivariant Quantum Neural Networkscited by 62
  6. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 60
  7. 2022Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networkscited by 52
  8. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  9. 2022Recent Advances for Quantum Neural Networks in Generative Learningcited by 39
  10. 2021Quantum machine learning with differential privacycited by 31
  11. 2022Benchmarking Adversarially Robust Quantum Machine Learning at Scalecited by 29
  12. 2021Automatic design of quantum feature mapscited by 28
38 more
  1. 2023Towards quantum enhanced adversarial robustness in machine learningcited by 28
  2. 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
  3. 2022Hybrid Quantum-Classical Generative Adversarial Network for High Resolution Image Generationcited by 22
  4. 2021Hybrid Quantum-Classical Graph Convolutional Networkcited by 21
  5. 2023Towards Quantum Federated Learningcited by 20
  6. 2023Quantum-Noise-Driven Generative Diffusion Modelscited by 20
  7. 2021Style-based quantum generative adversarial networks for Monte Carlo eventscited by 19
  8. 2021Variational inference with a quantum computercited by 18
  9. 2022Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noisecited by 18
  10. 2022Quantum Neural Architecture Search with Quantum Circuits Metric and Bayesian Optimizationcited by 16
  11. 2023MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computerscited by 16
  12. 2024Quantum Implicit Neural Representationscited by 16
  13. 2021Variational Quantum Soft Actor-Criticcited by 15
  14. 2022Reservoir Computing via Quantum Recurrent Neural Networkscited by 14
  15. 2023Quantum Machine Learning on Near-Term Quantum Devices: Current State of Supervised and Unsupervised Techniques for Real-World Applicationscited by 14
  16. 2021Learning quantum data with the quantum Earth Mover's distancecited by 13
  17. 2021Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designscited by 11
  18. 2023Statistical Complexity of Quantum Learningcited by 11
  19. 2025Quantum-PEFT: Ultra parameter-efficient fine-tuningcited by 11
  20. 2021Quantum Quantile Mechanics: Solving Stochastic Differential Equations for Generating Time-Seriescited by 10
  21. 2021Hybrid quantum-classical machine learning for generative chemistry and drug designcited by 10
  22. 2024Quantum Generative Diffusion Model: A Fully Quantum-Mechanical Model for Generating Quantum State Ensemblecited by 9
  23. 2023Successive Data Injection in Conditional Quantum GAN Applied to Time Series Anomaly Detectioncited by 8
  24. 2024Quantum State Generation with Structure-Preserving Diffusion Modelcited by 8
  25. 2021Representation of binary classification trees with binary features by quantum circuitscited by 7
  26. 2021Quantum Machine Learning for Financecited by 7
  27. 2021A Quantum Generative Adversarial Network for distributionscited by 7
  28. 2021Learnability of the output distributions of local quantum circuitscited by 7
  29. 2025Expressive equivalence of classical and quantum restricted Boltzmann machinescited by 7
  30. 2025Quantum-Informed Machine Learning for Predicting Spatiotemporal Chaos with Practical Quantum Advantagecited by 7
  31. 2022AutoQML: Automated Quantum Machine Learning for Wi-Fi Integrated Sensing and Communicationscited by 6
  32. 2023Quantum Generative Adversarial Networks: Bridging Classical and Quantum Realmscited by 6
  33. 2024Generating Universal Adversarial Perturbations for Quantum Classifierscited by 5
  34. 2024PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloudcited by 5
  35. 2025When Federated Learning Meets Quantum Computing: Survey and Research Opportunitiescited by 5
  36. 2021Quantum Model-Discoverycited by 4
  37. 2022Quantum Transfer Learning for Wi-Fi Sensingcited by 4
  38. 2022On Quantum Circuits for Discrete Graphical Modelscited by 4

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