145 citations · 718 across the 19 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
physics.comp-ph2020★ 62 cited
Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows
Suraj Pawar, Shady E. Ahmed, Omer San +2
Reduced rank nonlinear filters are increasingly utilized in data assimilation of geophysical flows, but often require a set of ensemble forward simulations to estimate forecast cov…
physics.flu-dyn2020★ 46 cited
An advanced hybrid deep adversarial autoencoder for parameterized nonlinear fluid flow modelling
M. Cheng, F. Fang, C. C. Pain +1
Considering the high computation cost produced in conventional computation fluid dynamic simulations, machine learning methods have been introduced to flow dynamic simulations in r…
physics.ao-ph2020★ 88 cited
Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network
M. Cheng, F. Fang, C. C. Pain +1
Deep learning techniques for improving fluid flow modelling have gained significant attention in recent years. Advanced deep learning techniques achieve great progress in rapidly p…