10 citations as recorded by crossref.

1. Stochastic‐Deep Learning Parameterization of Ocean Momentum Forcing A. Guillaumin & L. Zanna https://doi.org/10.1029/2021MS002534
2. Subgrid modelling for two-dimensional turbulence using neural networks R. Maulik et al. https://doi.org/10.1017/jfm.2018.770
3. Turbulence theories and statistical closure approaches Y. Zhou https://doi.org/10.1016/j.physrep.2021.07.001
4. Statistical Dynamics and Subgrid Modelling of Turbulence: From Isotropic to Inhomogeneous J. Frederiksen et al. https://doi.org/10.3390/atmos15080921
5. A formal derivation of the local energy transfer (LET) theory of homogeneous turbulence W. McComb & S. Yoffe https://doi.org/10.1088/1751-8121/aa8379
6. A novel dynamic framework for subgrid scale parametrization of mesoscale eddies in quasigeostrophic turbulent flows R. Maulik & O. San https://doi.org/10.1016/j.camwa.2017.04.016
7. Quasi-diagonal inhomogeneous closure for classical and quantum statistical dynamics J. Frederiksen https://doi.org/10.1063/1.5006938
8. Subgrid Parameterizations of the Eddy–Eddy, Eddy–Mean Field, Eddy–Topographic, Mean Field–Mean Field, and Mean Field–Topographic Interactions in Atmospheric Models V. Kitsios & J. Frederiksen https://doi.org/10.1175/JAS-D-18-0255.1
9. Jackson R. Herring and the Statistical Closure Problem of Turbulence: A Review of Renormalized Perturbation Theories D. McComb https://doi.org/10.3390/atmos14050827
10. Generalized Deconvolution Procedure for Structural Modeling of Turbulence O. San & P. Vedula https://doi.org/10.1007/s10915-017-0583-8