activity
20192021
most citedMachine learning algorithms for predicting the amplitude of chaotic laser pulses

71 citations · 83 across the 3 of their papers we have counts for

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5 papers · 1 filter

quant-ph2021

Dynamical phase transitions in quantum reservoir computing

Rodrigo Martínez-Peña, Gian Luca Giorgi, Johannes Nokkala +2

Closed quantum systems exhibit different dynamical regimes, like Many-Body Localization or thermalization, which determine the mechanisms of spread and processing of information. H…

quant-ph2021

Opportunities in Quantum Reservoir Computing and Extreme Learning Machines

Pere Mujal, Rodrigo Martínez-Peña, Johannes Nokkala +4

Quantum reservoir computing (QRC) and quantum extreme learning machines (QELM) are two emerging approaches that have demonstrated their potential both in classical and quantum mach…

quant-ph2020

Information Processing Capacity of Spin-Based Quantum Reservoir Computing Systems

R. Martínez-Peña, J. Nokkala, G. L. Giorgi +2

The dynamical behaviour of complex quantum systems can be harnessed for information processing. With this aim, quantum reservoir computing (QRC) with Ising spin networks was recent…

quant-ph2020

Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing

Johannes Nokkala, Rodrigo Martínez-Peña, Gian Luca Giorgi +3

We establish the potential of continuous-variable Gaussian states of linear dynamical systems for machine learning tasks. Specifically, we consider reservoir computing, an efficien…

quant-ph201912 cited

Machine learning applied to quantum synchronization-assisted probing

Gabriel Garau Estarellas, Gian Luca Giorgi, Miguel C. Soriano +1

A probing scheme is considered with an accessible and controllable qubit, used to probe an out-of equilibrium system consisting of a second qubit interacting with an environment. Q…