works on

From the 1 of 1.8k papers with an AI index.

output
20052026
most citedBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

24.4k citations

Showing 2021 · quant-phShow all

5 papers · 2 filters

quant-ph20211 cited

Revisiting dequantization and quantum advantage in learning tasks

Jordan Cotler, Hsin-Yuan Huang, Jarrod R. McClean

It has been shown that the apparent advantage of some quantum machine learning algorithms may be efficiently replicated using classical algorithms with suitable data access -- a pr…

quant-ph2021

Large scale multi-node simulations of gauge theory quantum circuits using Google Cloud Platform

Erik Gustafson, Burt Holzman, James Kowalkowski +12

Simulating quantum field theories on a quantum computer is one of the most exciting fundamental physics applications of quantum information science. Dynamical time evolution of qua…

quant-ph202116 cited

What the foundations of quantum computer science teach us about chemistry

Jarrod R. McClean, Nicholas C. Rubin, Joonho Lee +5

With the rapid development of quantum technology, one of the leading applications is the simulation of chemistry. Interestingly, even before full scale quantum computers are availa…

quant-ph202178 cited

Quantum circuit optimization with deep reinforcement learning

Thomas Fösel, Murphy Yuezhen Niu, Florian Marquardt +1

A central aspect for operating future quantum computers is quantum circuit optimization, i.e., the search for efficient realizations of quantum algorithms given the device capabili…

quant-ph2021124 cited

Removing leakage-induced correlated errors in superconducting quantum error correction

M. McEwen, D. Kafri, Z. Chen +48

Quantum computing can become scalable through error correction, but logical error rates only decrease with system size when physical errors are sufficiently uncorrelated. During co…