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Publications
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Welcome to the repository of QuASK's research publications. Explore our whitepapers and discover how to cite our main article. Additionally, find related works that have utilized QuASK, and learn how to add your research to our list for increased visibility.

Citing our article
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For proper citation of our flagship article in your research or publications, please use the following BibTeX format:

.. code-block:: bibtex

    @article{dimarcantonio2023quask,
        title={Quantum Advantage Seeker with Kernels (QuASK): a software framework to accelerate research in quantum machine learning},
        author={Di Marcantonio, Francesco and Incudini, Massimiliano and Tezza, Davide and Grossi, Michele},
        journal={Quantum Machine Intelligence},
        volume={5},
        number={1},
        pages={20},
        year={2023},
        publisher={Springer}
    }


Related works
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We are proud that several research projects have found QuASK invaluable. Some of these related works include:

- **Structure Learning of Quantum Embeddings**: M. Incudini, F. Martini, A. Di Pierro. *arXiv preprint* arXiv:2209.11144.

If your research also utilizes QuASK, we encourage you to share your work with us to be included in this list.

How to advertise your work with QuASK
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If you have incorporated QuASK into your project and would like to increase its visibility, we welcome you to add your research and a brief description to our list of related works. Contact us, and we will be delighted to include your contribution.

Your research becomes part of a growing ecosystem of knowledge and innovation.