mlsanityData to 7 Oct 2026

Quantum Graph Neural Networks

arXiv 1909.12264 ↗First posted 26 Sep 2019quant-ph cs.LGcited by 66

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Abstract (arXiv)

We introduce Quantum Graph Neural Networks (QGNN), a new class of quantum neural network ansatze which are tailored to represent quantum processes which have a graph structure, and are particularly suitable to be executed on distributed quantum systems over a quantum network. Along with this general class of ansatze, we introduce further specialized architectures, namely, Quantum Graph Recurrent Neural Networks (QGRNN) and Quantum Graph Convolutional Neural Networks (QGCNN). We provide four example applications of QGNNs: learning Hamiltonian dynamics of quantum systems, learning how to create multipartite entanglement in a quantum network, unsupervised learning for spectral clustering, and supervised learning for graph isomorphism classification.

Key facts. Cited by 66 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Sep 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 16; 2023: 10; 2024: 13; 2025: 13; 2026: 8.

66 papers.

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  1. 2023Challenges and Opportunities in Quantum Machine Learningcited by 202
  2. 2024Position: Topological Deep Learning is the New Frontier for Relational Learningcited by 65
  3. 2022Theory for Equivariant Quantum Neural Networkscited by 60
  4. 2022Group-Invariant Quantum Machine Learningcited by 56
  5. 2022Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networkscited by 52
  6. 2022Equivariant quantum circuits for learning on weighted graphscited by 41
  7. 2022Representation Theory for Geometric Quantum Machine Learningcited by 40
  8. 2022Recent Advances for Quantum Neural Networks in Generative Learningcited by 39
  9. 2023Machine Learning for Anomaly Detection in Particle Physicscited by 29
  10. 2021Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstructioncited by 20
  11. 2021Graph neural network initialisation of quantum approximate optimisationcited by 13
  12. 2023Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Datacited by 10
38 more
  1. 2024Reinforcement learning-assisted quantum architecture search for variational quantum algorithmscited by 10
  2. 2025A Primer on Quantum Machine Learningcited by 9
  3. 2021A Leap among Quantum Computing and Quantum Neural Networks: A Surveycited by 8
  4. 2022Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approachcited by 8
  5. 2023On the universality of Sn-equivariant k-body gatescited by 7
  6. 2024Trade-off between Gradient Measurement Efficiency and Expressivity in Deep Quantum Neural Networkscited by 7
  7. 2022AutoQML: Automated Quantum Machine Learning for Wi-Fi Integrated Sensing and Communicationscited by 6
  8. 2023Quantum Graph Learning: Frontiers and Outlookcited by 6
  9. 2023A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networkscited by 6
  10. 2024From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networkscited by 6
  11. 2023Time-Warping Invariant Quantum Recurrent Neural Networks via Quantum-Classical Adaptive Gatingcited by 5
  12. 2022From Quantum Graph Computing to Quantum Graph Learning: A Surveycited by 4
  13. 2022Quantum Transfer Learning for Wi-Fi Sensingcited by 4
  14. 2024Graph Neural Networks on Quantum Computerscited by 4
  15. 2024Resource-efficient equivariant quantum convolutional neural networkscited by 4
  16. 2022Training Hybrid Classical-Quantum Classifiers via Stochastic Variational Optimizationcited by 3
  17. 2022Classical ensemble of Quantum-classical ML algorithms for Phishing detection in Ethereum transaction networkscited by 3
  18. 2021QFCNN: Quantum Fourier Convolutional Neural Networkcited by 2
  19. 2021Equivariant Quantum Graph Circuitscited by 2
  20. 2022An Empirical Review of Optimization Techniques for Quantum Variational Circuitscited by 2
  21. 2022QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networkscited by 2
  22. 2024When Graph Neural Networks Meet Dynamic Mode Decompositioncited by 2
  23. 2024Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learningcited by 2
  24. 2025Adaptive Bayesian Single-Shot Quantum Sensingcited by 2
  25. 2026Q-AGNN: Quantum-Enhanced Attentive Graph Neural Network for Intrusion Detectioncited by 2
  26. 2022quEEGNet: Quantum AI for Biosignal Processingcited by 1
  27. 2023Learning Quantum Processes with Memory -- Quantum Recurrent Neural Networkscited by 1
  28. 2024A unifying primary framework for quantum graph neural networks from quantum graph statescited by 1
  29. 2024Hybrid Quantum Graph Neural Network for Molecular Property Predictioncited by 1
  30. 2024Graph Attention Hamiltonian Neural Networks: A Lattice System Analysis Model Based on Structural Learningcited by 1
  31. 2025Inductive Graph Representation Learning with Quantum Graph Neural Networkscited by 1
  32. 2025Learnable quantum spectral filters for hybrid graph neural networkscited by 1
  33. 2021Towards Efficient Ansatz Architecture for Variational Quantum Algorithmscited by 0
  34. 2022Extending Graph Transformers with Quantum Computed Aggregationcited by 0
  35. 2023Neural Crystalscited by 0
  36. 2023Quantum-classical simulation of quantum field theory by quantum circuit learningcited by 0
  37. 2024A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networkscited by 0
  38. 2024Lie-Equivariant Quantum Graph Neural Networkscited by 0

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