Jun 1, 2021 · Highlights. •. Human discovery of coarse-grained models is replaced with machine learning. •. Sparse regression is used to discover either an ...
Jan 30, 2020 · We replace the human discovery of such models, which typically involves spatial/stochastic averaging or coarse-graining, with a machine-learning ...
Feb 19, 2021 · We replace the human discovery of such models, which typically involves spatial/stochastic averaging or coarse-graining, with a machine-learning ...
Sep 6, 2023 · In this work, we leverage dimensionality reduction, sparse regression, and robust statistics to discover coarse-grained models of heterogeneous ...
May 23, 2022 · Abstract:We leverage data-driven model discovery methods to determine the governing equations for the emergent behavior of heterogeneous ...
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What is the data driven discovery of governing equations?
What is the coarse-grained strategy?
Sep 13, 2024 · We replace the human discovery of such models, which typically involves spatial/stochastic averaging or coarse-graining, with a machine-learning ...
Aug 31, 2023 · This thesis is centered around the application of machine learning techniques for uncovering hidden patterns and equations in complex physical systems.
Data-driven selection of coarse-grained models of coupled ...
link.aps.org › PhysRevResearch.2.043402
Dec 22, 2020 · This paper introduces a data-driven method for constructing reduced-order closure models for complex dynamical systems.
Oct 22, 2024 · Data-driven discovery of coarse-grained models is an active area of research, with recent works offering methods to discover hydrodynamic ...
In this paper, we advocate the paradigm of data-driven discovery for extract- ing governing equations by employing fine-scale simulation data. In particular, we ...