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20192023
most citedQuantum computing models for artificial neural networks

119 citations · 272 across the 12 of their papers we have counts for

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Showing 2022 · quant-phShow all

5 papers · 2 filters

quant-ph2022★ 1 cited

Robustness of quantum reinforcement learning under hardware errors

Andrea Skolik, Stefano Mangini, Thomas Bäck +2

Variational quantum machine learning algorithms have become the focus of recent research on how to utilize near-term quantum devices for machine learning tasks. They are considered…

quant-ph2022★ 29 cited

Entanglement entropy production in Quantum Neural Networks

Marco Ballarin, Stefano Mangini, Simone Montangero +2

Quantum Neural Networks (QNN) are considered a candidate for achieving quantum advantage in the Noisy Intermediate Scale Quantum computer (NISQ) era. Several QNN architectures have…

quant-ph2022★ 11 cited

Quantum variational learning for entanglement witnessing

Francesco Scala, Stefano Mangini, Chiara Macchiavello +2

Several proposals have been recently introduced to implement Quantum Machine Learning (QML) algorithms for the analysis of classical data sets employing variational learning means.…

quant-ph2022★ 1 cited

Quantum neural network autoencoder and classifier applied to an industrial case study

Stefano Mangini, Alessia Marruzzo, Marco Piantanida +3

Quantum computing technologies are in the process of moving from academic research to real industrial applications, with the first hints of quantum advantage demonstrated in recent…

quant-ph2022★ 15 cited

Qubit noise deconvolution

Stefano Mangini, Lorenzo Maccone, Chiara Macchiavello

We present a noise deconvolution technique to remove a wide class of noises when performing arbitrary measurements on qubit systems. In particular, we derive the inverse map of the…