119 citations · 272 across the 12 of their papers we have counts for
12 papers
Quantum State Reconstruction in a Noisy Environment via Deep Learning
Angela Rosy Morgillo, Stefano Mangini, Marco Piastra +1
Quantum noise is currently limiting efficient quantum information processing and computation. In this work, we consider the tasks of reconstructing and classifying quantum states c…
Variational quantum algorithms for machine learning: theory and applications
Stefano Mangini
This Ph.D. thesis provides a comprehensive review of the state-of-the-art in the field of Variational Quantum Algorithms and Quantum Machine Learning, including numerous original c…
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…
The Dawn of Quantum Natural Language Processing
Riccardo Di Sipio, Jia-Hong Huang, Samuel Yen-Chi Chen +2
In this paper, we discuss the initial attempts at boosting understanding human language based on deep-learning models with quantum computing. We successfully train a quantum-enhanc…
Variational learning for quantum artificial neural networks
Francesco Tacchino, Stefano Mangini, Panagiotis Kl. Barkoutsos +4
In the last few years, quantum computing and machine learning fostered rapid developments in their respective areas of application, introducing new perspectives on how information…
Quantum computing models for artificial neural networks
Stefano Mangini, Francesco Tacchino, Dario Gerace +2
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 quan…
Quantum computing model of an artificial neuron with continuously valued input data
Stefano Mangini, Francesco Tacchino, Dario Gerace +2
Artificial neural networks have been proposed as potential algorithms that could benefit from being implemented and run on quantum computers. In particular, they hold promise to gr…
Continuous Variable Quantum Perceptron
Fabio Benatti, Stefano Mancini, Stefano Mangini
We present a model of Continuous Variable Quantum Perceptron (CVQP) whose architecture implements a classical perceptron. The necessary non-linearity is obtained via measuring the…