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MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computers

arXiv 2308.11096 ↗First posted 22 Aug 2023quant-ph cs.AR cs.CVcited by 16

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Abstract (arXiv)

Quantum machine learning and vision have come to the fore recently, with hardware advances enabling rapid advancement in the capabilities of quantum machines. Recently, quantum image generation has been explored with many potential advantages over non-quantum techniques; however, previous techniques have suffered from poor quality and robustness. To address these problems, we introduce, MosaiQ, a high-quality quantum image generation GAN framework that can be executed on today's Near-term Intermediate Scale Quantum (NISQ) computers.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 11 of its 21 references that are in the map. First posted on arXiv 22 Aug 2023.

Builds on

11 of 21 references.

References · 11

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2022Generative Adversarial Networkscited by 5,627
  4. 2017Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithmscited by 4,349
  5. 2017Improved Training of Wasserstein GANscited by 2,235
  6. 2017Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkscited by 707
  7. 2018GANomaly: Semi-Supervised Anomaly Detection via Adversarial Trainingcited by 409
  8. 2018Quantum generative adversarial networkscited by 128
  9. 2020Experimental Quantum Generative Adversarial Networks for Image Generationcited by 83
  10. 2018Anomaly Detection with Generative Adversarial Networks for Multivariate Time Seriescited by 55
  11. 2022Hybrid Quantum-Classical Generative Adversarial Network for High Resolution Image Generationcited by 22

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 6; 2026: 5.

16 papers.

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  1. 2024Quantum Generative Diffusion Model: A Fully Quantum-Mechanical Model for Generating Quantum State Ensemblecited by 9
  2. 2024Robust Fitting on a Gate Quantum Computercited by 5
  3. 2024LatentQGAN: A Hybrid QGAN with Classical Convolutional Autoencodercited by 5
  4. 2025Quantum-enhanced Computer Vision: Going Beyond Classical Algorithmscited by 5
  5. 2024VAE-QWGAN: Addressing Mode Collapse in Quantum GANs via Autoencoding Priorscited by 2
  6. 2025EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Datacited by 2
  7. 2026End-to-End QGAN-Based Image Synthesis via Neural Noise Encoding and Intensity Calibrationcited by 2
  8. 2025ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computerscited by 1
  9. 2026Quantum Implicit Neural Representations for Novel View Synthesiscited by 1
  10. 2026Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generationcited by 1
  11. 2024OrganiQ: Mitigating Classical Resource Bottlenecks of Quantum Generative Adversarial Networks on NISQ-Era Machinescited by 0
  12. 2025QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptationcited by 0
4 more
  1. 2025MediQ-GAN: Quantum-Inspired GAN for High Resolution Medical Image Generationcited by 0
  2. 2025On the Generalization Limits of Quantum Generative Adversarial Networks with Pure State Generatorscited by 0
  3. 2026QTabGAN: A Hybrid Quantum-Classical GAN for Tabular Data Synthesiscited by 0
  4. 2026CoQui: A Coordinate-Conditioned Quantum Implicit Generative Adversarial Network for End-to-End Image Generationcited by 0