5 citations · 5 across the 1 of their papers we have counts for
4 papers
Provable superior accuracy in machine learned quantum models
Chengran Yang, Andrew Garner, Feiyang Liu +5
In modelling complex processes, the potential past data that influence future expectations are immense. Models that track all this data are not only computationally wasteful but al…
Quantum advantage in training binary neural networks
Yidong Liao, Daniel Ebler, Feiyang Liu +1
The performance of a neural network for a given task is largely determined by the initial calibration of the network parameters. Yet, it has been shown that the calibration, also r…
Learning Simon's quantum algorithm
Kwok Ho Wan, Feiyang Liu, Oscar Dahlsten +1
We consider whether trainable quantum unitaries can be used to discover quantum speed-ups for classical problems. Using methods recently developed for training quantum neural nets,…
On intelligent energy harvesting
Feiyang Liu, Yulong Zhang, Oscar Dahlsten +1
We probe the potential for intelligent intervention to enhance the power output of energy harvesters. We investigate general principles and a case study: a bi-resonant piezo electr…