17 citations · 17 across the 2 of their papers we have counts for
2 papers
quant-ph2024
Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm
Oleksandr Borysenko, Mykhailo Bratchenko, Ilya Lukin +4
A Quantum Natural Gradient (QNG) algorithm for optimization of variational quantum circuits has been proposed recently. In this study, we employ the Langevin equation with a QNG st…
stat.ML2020★ 17 cited
CoolMomentum: A Method for Stochastic Optimization by Langevin Dynamics with Simulated Annealing
Oleksandr Borysenko, Maksym Byshkin
Deep learning applications require global optimization of non-convex objective functions, which have multiple local minima. The same problem is often found in physical simulations…