51 citations · 286 across the 29 of their papers we have counts for
Showing 2019 · physics.comp-phShow all
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physics.comp-ph2019★ 24 cited
Turbulence forecasting via Neural ODE
Gavin D. Portwood, Peetak P. Mitra, Mateus Dias Ribeiro +9
Fluid turbulence is characterized by strong coupling across a broad range of scales. Furthermore, besides the usual local cascades, such coupling may extend to interactions that ar…
physics.comp-ph2019★ 13 cited
Leveraging Bayesian Analysis To Improve Accuracy of Approximate Models
Balasubramanya T. Nadiga, Chiyu Jiang, Daniel Livescu
We focus on improving the accuracy of an approximate model of a multiscale dynamical system that uses a set of parameter-dependent terms to account for the effects of unresolved or…