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Python 1.52% Jupyter Notebook 98.48%

dinae_4dvarnn_torch's Introduction

Pytorch code for the joint learning of variational models and associated solvers

Associated preprint: https://arxiv.org/abs/2006.03653

Content of the repository:

Directory TrainedModels: trained models for reproducing MNIST and Lorenz-96 results reported in the preprint
Notebooks notebookPyTorch_VarModelNN_*_Preprint2020: notebooks to repdoduce the results and figures in the preprint
Notebooks notebookPyTorch_DinAE_4DVarNN_*_GitOceaniX.ipynb: notebooks to the proposed framework on Lorenz_63, Lorenz-96 and MNIST datasets

License: CECILL-C license, see attached licence file.

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