15 citations as recorded by crossref.

1. A physics-inspired alternative to spatial filtering for large-eddy simulations of turbulent flows P. Johnson
2. Large eddy simulation of turbulent flow over a backward-facing step with a neural-network-based subgrid-scale model J. Park & H. Choi
3. A posteriori study on wall modeling in large eddy simulation using a nonlocal data-driven approach G. Tabe Jamaat et al.
4. Differentiable turbulence: Closure as a partial differential equation constrained optimization V. Shankar et al.
5. Large eddy simulation of flow over a circular cylinder with a neural-network-based subgrid-scale model M. Kim et al.
6. A recursive neural-network-based subgrid-scale model for large eddy simulation: application to homogeneous isotropic turbulence C. Cho et al.
7. Perspective on machine-learning-based large-eddy simulation H. Choi et al.
8. Frame invariant neural network closures for Kraichnan turbulence S. Pawar et al.
9. Neural networks for large eddy simulations of wall-bounded turbulence: numerical experiments and challenges M. Benjamin et al.
10. Two neural network Unet architecture for subfilter stress modeling A. Wu & S. Lele
11. Discretize first, filter next: Learning divergence-consistent closure models for large-eddy simulation S. Agdestein & B. Sanderse
12. Benchmarking of Machine Learning Ocean Subgrid Parameterizations in an Idealized Model A. Ross et al.
13. Learning physics-constrained subgrid-scale closures in the small-data regime for stable and accurate LES Y. Guan et al.
14. Challenges in the modeling and simulation of turbulent supercritical fluid flows and heat transfer T. Wan et al.
15. Nitrate isotopes in catchment hydrology: Insights, ideas and implications for models I. Matiatos et al.