7 papers · 1 filter
Assessing Projected Quantum Kernels for the Classification of IoT Data
Francesco D'Amore, Luca Mariani, Carlo Mastroianni +4
The use of quantum computing for machine learning is among the most promising applications of quantum technologies. Quantum models inspired by classical algorithms are developed to…
Efficient Variational Quantum Algorithms for the Generalized Assignment Problem
Carlo Mastroianni, Francesco Plastina, Jacopo Settino +1
Quantum algorithms offer a compelling new avenue for addressing difficult NP-complete optimization problems, such as the Generalized Assignment Problem (GAP). Given the operational…
Forecasting Low-Dimensional Turbulence via Multi-Dimensional Hybrid Quantum Reservoir Computing
L. Salatino, L. Mariani, A. Giordano +9
The prediction of complex dynamics remains an open problem across many domains of physics, where nonlinearities and multiscale interactions severely limit the reliability of conven…
Harnessing Quantum Extreme Learning Machines for image classification
A. De Lorenzis, M. P. Casado, M. P. Estarellas +5
Interest in quantum machine learning is increasingly growing due to its potential to offer more efficient solutions for problems that are difficult to tackle with classical methods…
Memory-Augmented Hybrid Quantum Reservoir Computing
J. Settino, L. Salatino, L. Mariani +9
Reservoir computing (RC) is an effective method for predicting chaotic systems by using a high-dimensional dynamic reservoir with fixed internal weights, while keeping the learning…
Variational Gibbs State Preparation on NISQ devices
Mirko Consiglio, Jacopo Settino, Andrea Giordano +6
The preparation of an equilibrium thermal state of a quantum many-body system on noisy intermediate-scale quantum (NISQ) devices is an important task in order to extend the range o…