mlsanityData to 7 Oct 2026

Federated Quantum Machine Learning

arXiv 2103.12010 ↗First posted 22 Mar 2021quant-ph cs.AI cs.CRcited by 82

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Abstract (arXiv)

Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects.

Key facts. Cited by 82 papers in the map (data through 7 Oct 2026). Builds on 52 of its 120 references that are in the map. First posted on arXiv 22 Mar 2021.

Builds on

52 of 120 references.

References · 52

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
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  12. 2015Deep Speech 2: End-to-End Speech Recognition in English and Mandarincited by 449
38 more
  1. 2019Federated Machine Learning: Concept and Applicationscited by 409
  2. 2019Federated Learning in Mobile Edge Networks: A Comprehensive Surveycited by 407
  3. 2020The power of quantum neural networkscited by 377
  4. 2019A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protectioncited by 371
  5. 2014Deep Speech: Scaling up end-to-end speech recognitioncited by 354
  6. 2019Parameterized quantum circuits as machine learning modelscited by 330
  7. 2019Robust Aggregation for Federated Learningcited by 314
  8. 2018Horovod: fast and easy distributed deep learning in TensorFlowcited by 275
  9. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 165
  10. 2020Survey of Personalization Techniques for Federated Learningcited by 144
  11. 2018An overview of deep learning in medical imaging focusing on MRIcited by 140
  12. 2018Quantum generative adversarial networkscited by 128
  13. 2019Convergence of Edge Computing and Deep Learning: A Comprehensive Surveycited by 120
  14. 2020Quantum Long Short-Term Memorycited by 118
  15. 2019BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learningcited by 115
  16. 2019Transfer learning in hybrid classical-quantum neural networkscited by 113
  17. 2018Blockchained On-Device Federated Learningcited by 105
  18. 2019Peer-to-peer Federated Learning on Graphscited by 85
  19. 2019Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networkscited by 79
  20. 2020Recurrent Quantum Neural Networkscited by 79
  21. 2021Noisy intermediate-scale quantum (NISQ) algorithmscited by 79
  22. 2020Reinforcement Learning with Quantum Variational Circuitscited by 74
  23. 2020Quantum Convolutional Neural Networks for High Energy Physics Data Analysiscited by 64
  24. 2019Decentralized Federated Learning: A Segmented Gossip Approachcited by 63
  25. 2020Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognitioncited by 56
  26. 2021An end-to-end trainable hybrid classical-quantum classifiercited by 49
  27. 2020FedCoin: A Peer-to-Peer Payment System for Federated Learningcited by 39
  28. 2019BAFFLE : Blockchain Based Aggregator Free Federated Learningcited by 38
  29. 2021Quantum Generative Models for Small Molecule Drug Discoverycited by 37
  30. 2019Robust Federated Learning with Noisy Communicationcited by 33
  31. 2020Hybrid quantum-classical classifier based on tensor network and variational quantum circuitcited by 26
  32. 2020Classification with Quantum Machine Learning: A Surveycited by 23
  33. 2021Hybrid Quantum-Classical Graph Convolutional Networkcited by 21
  34. 2018The Expressive Power of Parameterized Quantum Circuitscited by 18
  35. 2019Quantum Unsupervised and Supervised Learning on Superconducting Processorscited by 9
  36. 2021Decentralized Federated Learning Preserves Model and Data Privacycited by 8
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  38. 2020On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agendacited by 4

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 17; 2023: 12; 2024: 11; 2025: 25; 2026: 11.

82 papers.

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  1. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 58
  2. 2021Quantum Federated Learning with Quantum Datacited by 53
  3. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  4. 2022When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computingcited by 40
  5. 2022Systematic Literature Review: Quantum Machine Learning and its applicationscited by 32
  6. 2022PQLM -- Multilingual Decentralized Portable Quantum Language Model for Privacy Protectioncited by 26
  7. 2022Slimmable Quantum Federated Learningcited by 23
  8. 2022Quantum deep recurrent reinforcement learningcited by 23
  9. 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
  10. 2023Asynchronous training of quantum reinforcement learningcited by 20
  11. 2023Towards Quantum Federated Learningcited by 20
  12. 2024FedQNN: Federated Learning using Quantum Neural Networkscited by 20
38 more
  1. 2024QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detectioncited by 18
  2. 2023Federated Quantum Machine Learning with Differential Privacycited by 17
  3. 2022Non-IID Quantum Federated Learning with One-shot Communication Complexitycited by 15
  4. 2023Privacy-preserving quantum federated learning via gradient hidingcited by 15
  5. 2023Federated Quantum Long Short-term Memory (FedQLSTM)cited by 15
  6. 2022Federated Quantum Natural Gradient Descent for Quantum Federated Learningcited by 14
  7. 2022Reservoir Computing via Quantum Recurrent Neural Networkscited by 14
  8. 2023Optimizing Quantum Federated Learning Based on Federated Quantum Natural Gradient Descentcited by 14
  9. 2023Quantum Machine Learning on Near-Term Quantum Devices: Current State of Supervised and Unsupervised Techniques for Real-World Applicationscited by 14
  10. 2022Quantum Neural Network Classifiers: A Tutorialcited by 13
  11. 2022An Invitation to Distributed Quantum Neural Networkscited by 13
  12. 2022Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applicationscited by 12
  13. 2021PATE-AAE: Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classificationcited by 10
  14. 2021Quantum Quantile Mechanics: Solving Stochastic Differential Equations for Generating Time-Seriescited by 10
  15. 2024Consensus-based Distributed Quantum Kernel Learning for Speech Recognitioncited by 10
  16. 2025Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networkscited by 10
  17. 2023Expressive variational quantum circuits provide inherent privacy in federated learningcited by 8
  18. 2023Quantum Federated Learning With Quantum Networkscited by 8
  19. 2024Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving MLcited by 8
  20. 2024Federated Hierarchical Tensor Networks: a Collaborative Learning Quantum AI-Driven Framework for Healthcarecited by 7
  21. 2024Quantum delegated and federated learning via quantum homomorphic encryptioncited by 7
  22. 2024MQFL-FHE: Multimodal Quantum Federated Learning Framework with Fully Homomorphic Encryptioncited by 7
  23. 2025A Privacy-Preserving Federated Framework with Hybrid Quantum-Enhanced Learning for Financial Fraud Detectioncited by 7
  24. 2022Scalable Quantum Neural Networks for Classificationcited by 6
  25. 2023Quantum Federated Learning: Analysis, Design and Implementation Challengescited by 6
  26. 2025Experimentally validated quantum-secure federated learning over a multi-user quantum networkcited by 5
  27. 2025QFAL: Quantum Federated Adversarial Learningcited by 5
  28. 2025When Federated Learning Meets Quantum Computing: Survey and Research Opportunitiescited by 5
  29. 2022Projection Valued Measure-based Quantum Machine Learning for Multi-Class Classificationcited by 4
  30. 2022Quantum Split Neural Network Learning using Cross-Channel Poolingcited by 4
  31. 2022Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Codingcited by 4
  32. 2025Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligencecited by 4
  33. 2025Layerwise Federated Learning for Heterogeneous Quantum Clients using Quoruscited by 4
  34. 2025Towards Personalized Quantum Federated Learning for Anomaly Detectioncited by 4
  35. 2024Prospects of Privacy Advantage in Quantum Machine Learningcited by 3
  36. 2024Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data Sourcescited by 3
  37. 2025Introduction to Quantum Machine Learning and Quantum Architecture Searchcited by 3
  38. 2025Distributed Quantum Neural Networks on Distributed Photonic Quantum Computingcited by 3

50 most cited of 82 All 82 (JSON)