Physical invariance in neural networks for subgrid-scale scalar flux modeling

9 October 2020

Papers citing "Physical invariance in neural networks for subgrid-scale scalar flux modeling"

4 / 4 papers shown

Title
Explaining the physics of transfer learning a data-driven subgrid-scale closure to a different turbulent flow Adam Subel Yifei Guan A. Chattopadhyay P. Hassanzadeh AI4CE 29 41 0 07 Jun 2022
A posteriori learning for quasi-geostrophic turbulence parametrization Hugo Frezat Julien Le Sommer Ronan Fablet G. Balarac Redouane Lguensat 27 56 0 08 Apr 2022
Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning Said Ouala Steven L. Brunton A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet PINN AI4TS AI4CE 18 10 0 11 Feb 2022
A posteriori learning of quasi-geostrophic turbulence parametrization: an experiment on integration steps Hugo Frezat Julien Le Sommer Ronan Fablet G. Balarac Redouane Lguensat 33 2 0 12 Nov 2021