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Quantum computing models for artificial neural networks

Published 7 Feb 2021 in quant-ph | (2102.03879v2)

Abstract: Neural networks are computing models that have been leading progress in Machine Learning (ML) and AI applications. In parallel, the first small scale quantum computing devices have become available in recent years, paving the way for the development of a new paradigm in information processing. Here we give an overview of the most recent proposals aimed at bringing together these ongoing revolutions, and particularly at implementing the key functionalities of artificial neural networks on quantum architectures. We highlight the exciting perspectives in this context and discuss the potential role of near term quantum hardware in the quest for quantum machine learning advantage.

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