QuantumMachineLearningReviewPaperList

List of most cited 'Quantum Machine Learning' papers from Web of Science and QMI journal

1. Quantum circuit learning : K. Mitarai1, M. Negoro, M. Kitagawa, and K. Fujii, https://doi.org/10.1103/PhysRevA.98.032309

2. Quantum machine learning in feature Hilbert spaces: Maria Schuld, Nathan Killoran, https://doi.org/10.1103/PhysRevLett.122.040504

3. Parameterized quantum circuits as machine learning models: Marcello Benedetti, Erika Lloyd, Stefan Sack and Mattia Fiorentin, DOI 10.1088/2058-9565/ab4eb5

4. The power of quantum neural networks: Amira Abbas, David Sutter, Christa Zoufal, Aurelien Lucchi, Alessio Figalli & Stefan Woerner, https://doi.org/10.1038/s43588-021-00084-1

5. Power of data in quantum machine learning: Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven & Jarrod R. McClean, https://doi.org/10.1038/s41467-021-22539-9

6. Study on The Effect of Encoding Method in Quantum Machine Learning: Qingqing Xiong, Jinzhe Jiang, Chen Li, Xin Zhang, Yaqian Zhao, https://doi.org/10.1145/3651671.3651689

7. A rigorous and robust quantum speed-up in supervised machine learning: Yunchao Liu, Srinivasan Arunachalam & Kristan Temme, https://doi.org/10.1038/s41567-021-01287-z

8. Experimental Quantum Generative Adversarial Networks for Image Generation : He-Liang Huang, Yuxuan Du , Ming Gong, Youwei Zhao, Yulin Wu, Chaoyue Wang, Shaowei Li, Futian Liang, Jin Lin, Yu Xu, Rui Yang, Tongliang Liu, Min-Hsiu Hsieh, Hui Deng, Hao Rong, Cheng-Zhi Peng, Chao-Yang, Yu-Ao Chen, Dacheng Tao, Xiaobo Zhu, and Jian-Wei Pan, DOI10.1103/PhysRevApplied.16.024051

9. Towards quantum machine learning with tensor networks: William Huggins, Piyush Patil, Bradley Mitchell, K Birgitta Whaley and E Miles Stoudenmire, DOI 10.1088/2058-9565/aaea94

10. Exploiting symmetry in variational quantum machine learning: Johannes Jakob Meyer, Marian Mularski, Elies Gil-Fuster, Antonio Anna Mele, Francesco Arzani, Alissa Wilms, Jens Eisert, https://doi.org/10.1103/PRXQuantum.4.010328

11. Quantum convolutional neural network based on variational quantum circuits: Li-Hua Gong, Jun-Jie Pei, Tian-Feng Zhang, Nan-Run Zhou, https://doi.org/10.1016/j.optcom.2023.129993

12. Systematic literature review: Quantum machine learning and its applications: David Peral-García, Juan Cruz-Benito, Francisco José García-Peñalvo. https://doi.org/10.1016/j.cosrev.2024.100619

13. Quantum K-Nearest Neighbor Classification Algorithm via a Divide-and-Conquer Strategy: Li-Hua Gong, Wei Ding, Zi Li, Yuan-Zhi Wang, Nan-Run Zhou, https://doi.org/10.1002/qute.202300221

14. A quantum federated learning framework for classical clients: Yanqi Song, Yusen Wu, Shengyao Wu, Dandan Li, Qiaoyan Wen, Sujuan Qin & Fei Gao , https://doi.org/10.1007/s11433-023-2337-2

15. Quanvolutional neural networks: powering image recognition with quantum circuits: Maxwell Henderson, Samriddhi Shakya, Shashindra Pradhan & Tristan Cook, https://doi.org/10.1007/s42484-020-00012-y

16. Quantum convolutional neural network for classical data classification: Tak Hur, Leeseok Kim & Daniel K. Park, https://doi.org/10.1007/s42484-021-00061-x

17. Evaluation of parameterized quantum circuits: on the relation between classification accuracy, expressibility, and entangling capability: Thomas Hubregtsen, Josef Pichlmeier, Patrick Stecher & Koen Bertels, https://doi.org/10.1007/s42484-021-00038-w

18. Bayesian deep learning on a quantum computer: Zhikuan Zhao, Alejandro Pozas-Kerstjens, Patrick Rebentrost & Peter Wittek, https://doi.org/10.1007/s42484-019-00004-7

19. Subtleties in the trainability of quantum machine learning models: Supanut Thanasilp, Samson Wang, Nhat Anh Nghiem, Patrick Coles & Marco Cerezo, https://doi.org/10.1007/s42484-023-00103-6

20. Kernel methods in Quantum Machine Learning: Riccardo Mengoni & Alessandra Di Pierro, https://doi.org/10.1007/s42484-019-00007-4

21. Robust implementation of generative modeling with parametrized quantum circuits: Vicente Leyton-Ortega, Alejandro Perdomo-Ortiz & Oscar Perdomo, https://doi.org/10.1007/s42484-021-00040-2

22. Analysis and synthesis of feature map for kernel-based quantum classifier: Yudai Suzuki, Hiroshi Yano, Qi Gao, Shumpei Uno, Tomoki Tanaka, Manato Akiyama & Naoki Yamamoto, https://doi.org/10.1007/s42484-020-00020-y

23. QDNN: deep neural networks with quantum layers: Chen Zhao & Xiao-Shan Gao, https://doi.org/10.1007/s42484-021-00046-w

24. Layerwise learning for quantum neural networks: Andrea Skolik, Jarrod R. McClean, Masoud Mohseni, Patrick van der Smagt & Martin Leib, https://doi.org/10.1007/s42484-020-00036-4

25. Quantum transfer learning for breast cancer detection: Vanda Azevedo, Carla Silva & Inês Dutra , https://doi.org/10.1007/s42484-022-00062-4

26. Quantum-assisted associative adversarial network: applying quantum annealing in deep learning: Max Wilson, Thomas Vandal, Tad Hogg & Eleanor G. Rieffel, https://doi.org/10.1007/s42484-021-00047-9

27. Optimizing quantum heuristics with meta-learning: Max Wilson, Rachel Stromswold, Filip Wudarski, Stuart Hadfield, Norm M. Tubman & Eleanor G. Rieffel, https://doi.org/10.1007/s42484-020-00022-w

28. A case study for cyber-attack detection using quantum variational circuits: Maximilian Moll & Leonhard Kunczik, https://doi.org/10.1007/s42484-025-00277-1

29. Network attack traffic detection with hybrid quantum-enhanced convolution neural network: Zihao Wang, Kar Wai Fok & Vrizlynn L. L. Thing, https://doi.org/10.1007/s42484-025-00278-0

30. Quantum adversarial learning for kernel methods: Giuseppe Montalbano & Leonardo Banchi, https://doi.org/10.1007/s42484-025-00238-8