Data_driven_symbolic_regression
Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used to identify physical process, numerical schemes, and LES subgrid scale (eddy viscosity) turbulence models.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pinns | 387 | 4 years ago | 13 | mit | Python | |||||
| Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations | ||||||||||
| Lauztat | 14 | 4 years ago | 8 | June 18, 2019 | bsd-3-clause | Python | ||||
| Pure python statistic tools for high energy physics. | ||||||||||
| Data_driven_symbolic_regression | 7 | 3 years ago | gpl-3.0 | Python | ||||||
| Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used to identify physical process, numerical schemes, and LES subgrid scale (eddy viscosity) turbulence models. | ||||||||||
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