Variational learning for quantum artificial neural networks
Francesco Tacchino, Panagiotis Kl. Barkoutsos, et al.
QCE 2020
Neural networks are computing models that have been leading progress in Machine Learning (ML) and Artificial Intelligence (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.
Francesco Tacchino, Panagiotis Kl. Barkoutsos, et al.
QCE 2020
Gabriele Agliardi, Giorgio Cortiana, et al.
npj Quantum Information
Waheeda Banu Saib, Kenny Choo, et al.
QIP 2022
Alistair Letcher, Stefan Woerner, et al.
QTML 2023