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pro vyhledávání: '"Placidi, Leonardo"'
Autor:
Placidi, Leonardo, Hataya, Ryuichiro, Mori, Toshio, Aoyama, Koki, Morisaki, Hayata, Mitarai, Kosuke, Fujii, Keisuke
We introduce the first large-scale dataset, MNISQ, for both the Quantum and the Classical Machine Learning community during the Noisy Intermediate-Scale Quantum era. MNISQ consists of 4,950,000 data points organized in 9 subdatasets. Building our dat
Externí odkaz:
http://arxiv.org/abs/2306.16627
Quantum machine learning has the potential to computationally outperform classical machine learning, but it is not yet clear whether it will actually be valuable for practical problems. While some artificial scenarios have shown that certain quantum
Externí odkaz:
http://arxiv.org/abs/2302.09751
Autor:
Franco, Luca, Placidi, Leonardo, Giuliari, Francesco, Hasan, Irtiza, Cristani, Marco, Galasso, Fabio
Transformer Networks have established themselves as the de-facto state-of-the-art for trajectory forecasting but there is currently no systematic study on their capability to model the motion patterns of people, without interactions with other indivi
Externí odkaz:
http://arxiv.org/abs/2203.11878
Autor:
Franco, Luca, Placidi, Leonardo, Giuliari, Francesco, Hasan, Irtiza, Cristani, Marco, Galasso, Fabio
Publikováno v:
In Pattern Recognition June 2023 138