62 citations · 135 across the 4 of their papers we have counts for
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physics.comp-ph2021★ 14 cited
A data driven reduced order model of fluid flow by Auto-Encoder and self-attention deep learning methods
R. Fu, D. Xiao, I. M. Navon +1
This paper presents a new data-driven non-intrusive reduced-order model(NIROM) that outperforms the traditional Proper orthogonal decomposition (POD) based reducedorder model. This…
physics.comp-ph2021
A nonintrusive hybrid neural-physics modeling of incomplete dynamical systems: Lorenz equations
Suraj Pawar, Omer San, Adil Rasheed +1
This work presents a hybrid modeling approach to data-driven learning and representation of unknown physical processes and closure parameterizations. These hybrid models are suitab…
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…