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20182024
most citedCompressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence

58 citations · 115 across the 5 of their papers we have counts for

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Showing 2019Show all

2 papers · 1 filter

physics.comp-ph2019

Time-series learning of latent-space dynamics for reduced-order model closure

Romit Maulik, Arvind Mohan, Bethany Lusch +3

We study the performance of long short-term memory networks (LSTMs) and neural ordinary differential equations (NODEs) in learning latent-space representations of dynamical equatio…

physics.flu-dyn2019★ 58 cited

Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence

Arvind Mohan, Don Daniel, Michael Chertkov +1

High-fidelity modeling of turbulent flows is one of the major challenges in computational physics, with diverse applications in engineering, earth sciences and astrophysics, among…