119 citations · 272 across the 12 of their papers we have counts for
5 papers · 1 filter
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…
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…
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.…
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…
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…