Datasets:
Tasks:
Image-to-3D
Size:
1K<n<10K
ArXiv:
Tags:
mathematics
partial-differential-equations
computational fluid dynamics
physics
neural operator
DOI:
License:
Add link to paper
Browse filesThis PR ensures the dataset is linked to (and can be found at) https://huggingface.co/papers/2405.17211
README.md
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---
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license: mit
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task_categories:
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- image-to-3d
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tags:
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- computational fluid dynamics
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- physics
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- neural operator
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size_categories:
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- 1K<n<10K
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---
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# Navier Stokes Dataset of Isotropic Turbulence in a periodic box
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<!-- Provide a quick summary of the dataset. -->
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<!-- Provide the basic links for the dataset. -->
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- **Repository:** [https://github.com/scaomath/torch-cfd](https://github.com/scaomath/torch-cfd)
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- **Paper:** [
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- **Demo:**
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- [The classical Kolmogorov inverse cascade with a solenoidal forcing and small drag.](https://github.com/scaomath/torch-cfd/blob/main/examples/Kolmogrov2d_rk4_cn_forced_turbulence.ipynb)
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- [The fast training using the data with a small number of vortices.](https://github.com/scaomath/torch-cfd/blob/main/examples/ex2_SFNO_train_fnodata.ipynb)
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year={2024},
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primaryClass={cs.LG}
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}
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```
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---
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license: mit
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size_categories:
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- 1K<n<10K
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task_categories:
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- image-to-3d
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tags:
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- computational fluid dynamics
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- physics
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- neural operator
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---
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# Navier Stokes Dataset of Isotropic Turbulence in a periodic box
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<!-- Provide a quick summary of the dataset. -->
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<!-- Provide the basic links for the dataset. -->
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- **Repository:** [https://github.com/scaomath/torch-cfd](https://github.com/scaomath/torch-cfd)
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- **Paper:** [Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent Flows](https://huggingface.co/papers/2405.17211)
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- **Demo:**
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- [The classical Kolmogorov inverse cascade with a solenoidal forcing and small drag.](https://github.com/scaomath/torch-cfd/blob/main/examples/Kolmogrov2d_rk4_cn_forced_turbulence.ipynb)
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- [The fast training using the data with a small number of vortices.](https://github.com/scaomath/torch-cfd/blob/main/examples/ex2_SFNO_train_fnodata.ipynb)
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year={2024},
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primaryClass={cs.LG}
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}
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```
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