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🔄 Quantum Transfer Learning (QTL) Papers
This section of the Quantum AI Papers repository focuses on Quantum Transfer Learning (QTL).
QTL leverages knowledge from pre-trained quantum or hybrid quantum-classical models and adapts it to new tasks or domains. This paradigm plays a crucial role in overcoming limitations of small datasets, reducing training costs, and accelerating the deployment of quantum-enhanced AI systems.
📚 Scope
Research papers in this category explore:
- Transfer of learned quantum circuit parameters between tasks
- Hybrid classical–quantum transfer learning frameworks
- Applications of QTL in physics, chemistry, medical imaging, and natural language processing
- Optimization strategies to mitigate issues such as barren plateaus
- Cross-domain transfer of quantum models for practical real-world problems
🗂️ Papers List
| title | year | publisher | Author | link | category |
|---|---|---|---|---|---|
| Quantum transfer learning for acceptability judgements | 2024 | Quantum Machine Intelligence | Buonaiuto, Giuseppe, et al. | https://link.springer.com/article/10.1007/s42484-024-00141-8 | QTL |
| Transfer learning from Hermitian to non-Hermitian quantum many-body physics | 2024 | Journal of Physics: Condensed Matter | Sayyad, Sharareh, and Jose L. Lado. | https://iopscience.iop.org/article/10.1088/1361-648X/ad22f8/meta | QTL |
| Hybrid classical-quantum transfer learning for text classification | 2024 | Quantum Machine Intelligence | Ardeshir-Larijani, Ebrahim, and Mohammad Mahdi Nasiri Fatmehsari. | https://link.springer.com/article/10.1007/s42484-024-00147-2 | QTL |
| Detecting quantum phase transitions in a frustrated spin chain via transfer learning of a quantum classifier algorithm | 2024 | Physical Review A | Ferreira-Martins, André J., et al. | https://journals.aps.org/pra/abstract/10.1103/PhysRevA.109.052623 | QTL |
| Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification | 2024 | arXiv | Chan, Skylar, et al. | https://arxiv.org/pdf/2405.00156 | QTL |
| Transfer learning in predicting quantum many-body dynamics: from physical | 2024 | arXiv | Schmidt, Philipp, Florian Marquardt, and Naeimeh Mohseni. | https://arxiv.org/pdf/2405.16254 | QTL |
| observables to entanglement entropy | |||||
| Transfer Learning Based Hybrid Quantum Neural Network Model for Surface Anomaly Detection | 2024 | EEE Computer Society Annual Symposium on VLSI (ISVLSI). | Bhowmik, Sounak, and Himanshu Thapliyal. | https://ieeexplore.ieee.org/abstract/document/10682710 | QTL |
| A Novel Classical-Quantum Transfer Learning Framework for Image Recognition | 2024 | Available at SSRN | Ruan, Banyao, Zhihao Liu, and Xi Li. | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4806924 | QTL |
| Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting | 2024 | Nature Communications | Buterez, David, et al. | https://www.nature.com/articles/s41467-024-45566-8 | QTL |
| Transfer learning of optimal QAOA parameters in combinatorial optimization | 2024 | arXiv | Montanez-Barrera, J. A., Dennis Willsch, and Kristel Michielsen. | https://arxiv.org/pdf/2402.05549 | QTL |
| Quantum Federated Learning with Quantum Networks | 2024 | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). | Wang, Tyler, Huan-Hsin Tseng, and Shinjae Yoo. | https://ieeexplore.ieee.org/abstract/document/10447516 | QTL |
| Hybrid Quantum Classical Machine Learning with Knowledge Distillation | 2024 | IEEE International Conference on Communications | Li, Mingze, et al. | https://ieeexplore.ieee.org/abstract/document/10622755 | QTL |
| Classical-to-quantum convolutional neural network transfer learning | 2023 | ScienceDirect | Juhyeon Kim, Joonsuk Huh, Daniel K. Park | https://doi.org/10.1016/j.neucom.2023.126643 | QTL |
| Mitigating barren plateaus with transfer-learning-inspired parameter initializations | 2023 | IOPScience | Huan-Yu Liu, Tai-Ping Sun, Yu-Chun Wu, Yong-Jian Han, Guo-Ping Guo | https://doi.org/10.1088/1367-2630/acb58e | QTL |
| Implementing Magnetic Resonance Imaging Brain Disorder Classification via AlexNet–Quantum Learning | 2023 | MDPI | by Naif Alsharabi, Tayyaba Shahwar, Ateeq Ur Rehman, Yasser Alharbi | https://doi.org/10.3390/math11020376 | QTL |
| Transformer quantum state: A multipurpose model for quantum many-body problems | 2023 | APS : Physical Review B | Yuan-Hang Zhang, Massimiliano Di Ventra | https://doi.org/10.1103/PhysRevB.107.075147 | QTL |
| covering condensed matter and materials physics | |||||
| Quantum boosting using domain-partitioning hypotheses | 2023 | Springer | Sagnik Chatterjee, Rohan Bhatia, Parmeet Singh Chani, Debajyoti Bera | https://doi.org/10.1007/s42484-023-00122-3 | QTL |
| Jun Qi; Javier Tejedor | 2022 | International Conference on Acoustics, Speech, and Signal Processing (ICASSP) - IEEE | Jun Qi; Javier Tejedor | https://ieeexplore.ieee.org/abstract/document/9747636 | QTL |
| Muhammad Junaid Umer, Javeria Amin, Muhammad Sharif, Muhammad Almas Anjum, Faisal Azam, Jamal Hussain Shah | 2022 | Wiley | Muhammad Junaid Umer, Javeria Amin, Muhammad Sharif, Muhammad Almas Anjum, Faisal Azam, Jamal Hussain Shah | https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.6434 | QTL |
| Kanimozhi T; Sridevi S; Tirumalanadhuni Siva Manikumar; Tallam Dheeraj; Amaravathi Sumanth | 2022 | 2022 International Conference on Innovative Trends in Information Technology (ICITIIT) | Kanimozhi T; Sridevi S; Tirumalanadhuni Siva Manikumar; Tallam Dheeraj; Amaravathi Sumanth | https://ieeexplore.ieee.org/abstract/document/9744220 | QTL |
| Javeria Amin, Muhammad Almas Anjum, Muhammad Sharif, Saima Jabeen, Seifedine Kadry, Pablo Moreno Ger | 2022 | Computational Intelligence and Neuroscience | Javeria Amin, Muhammad Almas Anjum, Muhammad Sharif, Saima Jabeen, Seifedine Kadry, Pablo Moreno Ger | https://onlinelibrary.wiley.com/doi/full/10.1155/2022/3236305 | QTL |
| Nikhil Venkat Kumsetty; Amith Bhat Nekkare; Sowmya Kamath S.; Anand Kumar M. | 2022 | 2022 31st Conference of Open Innovations Association (FRUCT) | Nikhil Venkat Kumsetty; Amith Bhat Nekkare; Sowmya Kamath S.; Anand Kumar M. | https://ieeexplore.ieee.org/abstract/document/9770922 | QTL |
| Sridevi S; Kanimozhi T; Sayantan Bhattacharjee; Durri Shahwar; K. Soma Sekhar Reddy | 2022 | 2022 International Conference on Innovative Trends in Information Technology (ICITIIT) | Sridevi S; Kanimozhi T; Sayantan Bhattacharjee; Durri Shahwar; K. Soma Sekhar Reddy | https://ieeexplore.ieee.org/abstract/document/9744184 | QTL |
| Amna Mir1 , Umer Yasin1 , Salman Naeem Khan1 , Atifa Athar3, *, Riffat Jabeen 2 and Sehrish Aslam | 2022 | Computers, Materials & Continua | Amna Mir1 , Umer Yasin1 , Salman Naeem Khan1 , Atifa Athar3, *, Riffat Jabeen 2 and Sehrish Aslam | https://www.researchgate.net/profile/Riffat-Jabeen/publication/356999322_Diabetic_Retinopathy_Detection_Using_Classical-Quantum_Transfer_Learning_Approach_and_Probability_Model/links/61b77b984b318a6970db409e/Diabetic-Retinopathy-Detection-Using-Classical-Quantum-Transfer-Learning-Approach-and-Probability-Model.pdf | QTL |
| Bishwas Mishra, Abhishek Samanta | 2022 | Sparklinglight Transactions on Artificial Intelligence and Quantum Computing | Bishwas Mishra, Abhishek Samanta | https://sparklinglightpublisher.com/index.php/slp/article/view/25 | QTL |
| Haorong Zhao, Xing Deng, Zhai Patrick, Yingtao Jiang, Haijian Shao | 2022 | researchsquare | Haorong Zhao, Xing Deng, Zhai Patrick, Yingtao Jiang, Haijian Shao | https://www.researchsquare.com/article/rs-1807201/v1 | QTL |
| Sharu Theresa Jose and Osvaldo Simeone | 2022 | researchgate | Sharu Theresa Jose and Osvaldo Simeone | https://www.researchgate.net/profile/Sharu-Theresa-Jose-2/publication/357928129_Transfer_Learning_in_Quantum_Parametric_Classifiers_An_Information-Theoretic_Generalization_Analysis/links/61ea7a298d338833e3851241/Transfer-Learning-in-Quantum-Parametric-Classifiers-An-Information-Theoretic-Generalization-Analysis.pdf | QTL |
| Senthilkumar Vijayakumar; Filious Louis; Shaunak Pai Kane; Jeevarathinam Balachandar | 2022 | Quantum Computing and Engineering (QCE), IEEE International Conference | Senthilkumar Vijayakumar; Filious Louis; Shaunak Pai Kane; Jeevarathinam Balachandar | https://ieeexplore.ieee.org/abstract/document/9951217 | QTL |
| Harshit Mogalapalli; Mahesh Abburi; B. Nithya; Surya Kiran Vamsi Bandreddi | 2022 | AIP Conference Proceedings | Harshit Mogalapalli; Mahesh Abburi; B. Nithya; Surya Kiran Vamsi Bandreddi | https://pubs.aip.org/aip/acp/article-abstract/2424/1/070003/2822279/Trash-classification-using-quantum-transfer | QTL |
| T. Tamilvizhi, R. Surendran, K. Anbazhagan, K. Rajkumar | 2022 | Mathematical Problems in Engineering | T. Tamilvizhi, R. Surendran, K. Anbazhagan, K. Rajkumar | https://onlinelibrary.wiley.com/doi/full/10.1155/2022/3452413 | QTL |
| Dejun Jiang, Huiyong Sun , Jike Wang†, Chang-Yu Hsieh, Yuquan Li, Zhenxing Wu, Dongsheng Cao , Jian Wu and Tingjun Hou | 2022 | Briefings in Bioinformatics | Dejun Jiang, Huiyong Sun , Jike Wang†, Chang-Yu Hsieh, Yuquan Li, Zhenxing Wu, Dongsheng Cao , Jian Wu and Tingjun Hou | https://academic.oup.com/bib/article/23/2/bbab597/6513729 | QTL |
| Toshiaki Koike-Akino; Pu Wang; Ye Wang | 2022 | IEEE International Conference on Communications (ICC) | Toshiaki Koike-Akino; Pu Wang; Ye Wang | https://ieeexplore.ieee.org/abstract/document/9839011 | QTL |
| Vanda Azevedo, Carla Silva & Inês Dutra | 2022 | Quantum Machine Intelligence | Vanda Azevedo, Carla Silva & Inês Dutra | https://link.springer.com/article/10.1007/s42484-022-00062-4 | QTL |
| Pumal Dahal , Basanta Joshi | 2022 | Proceedings of 12th IOE Graduate Conference | Pumal Dahal , Basanta Joshi | http://conference.ioe.edu.np/publications/ioegc12/IOEGC-12-214-12315.pdf | QTL |
🔗 Cross-References
- Quantum Computing Fundamentals
- Quantum Machine Learning
- Quantum Neural Networks and Quantum Recurrent Neural Networks
- Quantum Convolutional Neural Networks
- Quantum Reinforcement Learning
- Quantum Generative Models
- Quantum Diffusion Models
- Quantum Graph Learning
- Quantum Natural Language Processing
- Quantum Transfer Learning
🤝 Contributions
Contributions are welcome! Please ensure that new entries include:
- Correct metadata (title, year, authors, publisher, link)
- Category tag (
QTL) - Optional short summary of the contribution
Authors and contributors
- Ali Akbar Kiaei — repository engineering, automation, metadata tooling, CI, and release management
- Mahnaz Bush — systematic literature review, paper screening, scientific taxonomy, curation, and documentation
- Raha Aghaei — bibliographic validation, metadata quality assurance, duplicate detection, link verification, and reproducibility
QAI-brain Research Collection
This repository is part of the QAI-brain open research and software collection. Browse the central Quantum AI paper index for related topics and repositories.