127 citations · 762 across the 47 of their papers we have counts for
Showing 2020 · physics.comp-phShow all
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physics.comp-ph2020★ 36 cited
Interpreting neural network models of residual scalar flux
Gavin D. Portwood, Balasubramanya T. Nadiga, Juan A. Saenz +1
We show that in addition to providing effective and competitive closures, when analysed in terms of dynamics and physically-relevant diagnostics, artificial neural networks (ANNs)…
physics.comp-ph2020★ 48 cited
Embedding Hard Physical Constraints in Neural Network Coarse-Graining of 3D Turbulence
Arvind T. Mohan, Nicholas Lubbers, Daniel Livescu +1
In the recent years, deep learning approaches have shown much promise in modeling complex systems in the physical sciences. A major challenge in deep learning of PDEs is enforcing…