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Classification with Integrated Quantum and Spiking Neural Networks / Pasquali, Dominic (UC, Santa Cruz ; CERN) ; Grossi, Michele (CERN) ; Vallecorsa, Sofia (CERN)
Spiking neural networks are rapidly gaining interest in analogue computation. So far little work has been conducted in blending quantum and spiking neural network methods into machine learning models. [...]
2023 - 2 p. - Published in : 10.1109/QCE57702.2023.10251
In : 2023 International Conference on Quantum Computing and Engineering (QCE23), Bellevue, United States, 17 - 22 Sep 2023, pp.298-299

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Measurements With A Quantum Vision Transformer: A Naive Approach / Pasquali, Dominic (UC, Santa Cruz ; CERN) ; Grossi, Michele (CERN) ; Vallecorsa, Sofia (CERN)
In mainstream machine learning, transformers are gaining widespread usage. As Vision Transformers rise in popularity in computer vision, they now aim to tackle a wide variety of machine learning applications. [...]
2024 - 8 p. - Published in : EPJ Web Conf. 295 (2024) 12003 Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023, pp.12003

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Classification With Unimodular Matrices In Hybrid Models / Pasquali, Dominic (UC, Santa Cruz ; CERN)
Guessing the architecture of a variational quantum circuit can be fraught with error, since determining the correct locations and types of parameterized quantum gates is often an empirical task. This work demonstrates that using a general parameterized unimodular matrix achieves a higher classification accuracy faster than comparable classical models. [...]
2022 - 6 p. - Published in : 10.1109/SEC54971.2022.00063
In : 2022 IEEE/ACM 7th Symposium on Edge Computing (SEC 2022), Seattle, Washington, United States, 5 - 8 Dec 2022, pp.420-425

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