58 citations · 113 across the 15 of their papers we have counts for
3 papers · 1 filter
State estimation with quantum extreme learning machines beyond the scrambling time
Marco Vetrano, Gabriele Lo Monaco, Luca Innocenti +2
Quantum extreme learning machines (QELMs) leverage untrained quantum dynamics to efficiently process information encoded in input quantum states, avoiding the high computational co…
Quantum Extreme Learning of molecular potential energy surfaces and force fields
Gabriele Lo Monaco, Marco Bertini, Salvatore Lorenzo +1
Quantum machine learning algorithms are expected to play a pivotal role in quantum chemistry simulations in the immediate future. One such key application is the training of a quan…
The importance of using the averaged mutual information when quantifying quantum objectivity
Diana A. Chisholm, Luca Innocenti, G. Massimo Palma
In the context of quantum objectivity, a standard way to quantify the classicality of a state is via the mutual information between a system and different fractions of its environm…