432 citations · 2.1k across the 56 of their papers we have counts for
3 papers · 2 filters
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…
On defining the Hamiltonian beyond quantum theory
Dominic Branford, Oscar C. O. Dahlsten, Andrew J. P. Garner
Energy is a crucial concept within classical and quantum physics. An essential tool to quantify energy is the Hamiltonian. Here, we consider how to define a Hamiltonian in general…
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,…