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pro vyhledávání: '"Kazdaghli, Skander"'
Autor:
Coyle, Brian, Cherrat, El Amine, Jain, Nishant, Mathur, Natansh, Raj, Snehal, Kazdaghli, Skander, Kerenidis, Iordanis
Quantum machine learning requires powerful, flexible and efficiently trainable models to be successful in solving challenging problems. In this work, we present density quantum neural networks, a learning model incorporating randomisation over a set
Externí odkaz:
http://arxiv.org/abs/2405.20237
Autor:
Thakkar, Sohum, Kazdaghli, Skander, Mathur, Natansh, Kerenidis, Iordanis, Ferreira-Martins, André J., Brito, Samurai
Quantum algorithms have the potential to enhance machine learning across a variety of domains and applications. In this work, we show how quantum machine learning can be used to improve financial forecasting. First, we use classical and quantum Deter
Externí odkaz:
http://arxiv.org/abs/2306.12965
Imputing data is a critical issue for machine learning practitioners, including in the life sciences domain, where missing clinical data is a typical situation and the reliability of the imputation is of great importance. Currently, there is no canon
Externí odkaz:
http://arxiv.org/abs/2303.17893
Autor:
Landman, Jonas, Mathur, Natansh, Li, Yun Yvonna, Strahm, Martin, Kazdaghli, Skander, Prakash, Anupam, Kerenidis, Iordanis
Publikováno v:
Quantum 6, 881 (2022)
Quantum machine learning techniques have been proposed as a way to potentially enhance performance in machine learning applications. In this paper, we introduce two new quantum methods for neural networks. The first one is a quantum orthogonal neural
Externí odkaz:
http://arxiv.org/abs/2212.07389
Autor:
Mathur, Natansh, Landman, Jonas, Li, Yun Yvonna, Strahm, Martin, Kazdaghli, Skander, Prakash, Anupam, Kerenidis, Iordanis
Machine Learning provides powerful tools for a variety of applications, including disease diagnosis through medical image classification. In recent years, quantum machine learning techniques have been put forward as a way to potentially enhance perfo
Externí odkaz:
http://arxiv.org/abs/2109.01831
Akademický článek
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Autor:
Thakkar, Sohum, Kazdaghli, Skander, Mathur, Natansh, Kerenidis, Iordanis, Ferreira–Martins, André J., Brito, Samurai
Publikováno v:
Quantum Machine Intelligence; June 2024, Vol. 6 Issue: 1