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20042025
most citedSubgrid-scale parametrization of unresolved scales in forced Burgers equation using Generative Adversarial Networks (GAN)

10 citations · 33 across the 24 of their papers we have counts for

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physics.comp-ph2024

Application of Machine Learning and Convex Limiting to Subgrid Flux Modeling in the Shallow-Water Equations

Ilya Timofeyev, Alexey Schwarzmann, Dmitri Kuzmin

We propose a combination of machine learning and flux limiting for property-preserving subgrid scale modeling in the context of flux-limited finite volume methods for the one-dimen…

physics.comp-ph2020★ 10 cited

Subgrid-scale parametrization of unresolved scales in forced Burgers equation using Generative Adversarial Networks (GAN)

Jeric Alcala, Ilya Timofeyev

Stochastic subgrid-scale parametrizations aim to incorporate effects of unresolved processes in an effective model by sampling from a distribution usually described in terms of res…