tdma-practical-session
Practical session at the summer school "TDMA"
Science Score: 67.0%
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Low similarity (6.8%) to scientific vocabulary
Repository
Practical session at the summer school "TDMA"
Basic Info
- Host: GitHub
- Owner: cerea-daml
- License: mit
- Language: Jupyter Notebook
- Default Branch: master
- Size: 21.5 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 1
Metadata Files
README.md
Introduction to surrogate modelling in the geosciences
Marc Bocquet¹ marc.bocquet@enpc.fr and Alban Farchi¹ alban.farchi@enpc.fr
(1) CEREA, École des Ponts and EdF R&D, IPSL, Île-de-France, France
During this session, we will apply standard machine learning methods to learn the dynamics of the Lorenz 1996 model. The objective here is to get a preview of how machine learning can be applied to geoscientific models in a low-order models where testing is quick.
These practical sessions are part of the TDMA summer school held in 2023 in Grenoble, France.
Installation
Install conda, for example through miniconda or through mamba.
Clone the repertory:
$ git clone git@github.com:cerea-daml/tdma-practical-session.git
Go to the repertory. Once there, create a dedicated anaconda environment for the sessions:
$ conda env create -f environment.yaml
Activate the newly created environment:
$ conda activate tdma
Open the notebook (e.g. with Jupyter) and follow the instructions:
$ jupyter-notebook questions.ipynb
Owner
- Name: CEREA DA-ML team
- Login: cerea-daml
- Kind: organization
- Location: Paris, France
- Website: https://www.cerea-lab.fr
- Repositories: 2
- Profile: https://github.com/cerea-daml
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Farchi" given-names: "Alban" orcid: "https://orcid.org/0000-0002-4162-8289" - family-names: "Bocquet" given-names: "Marc" title: "Introduction to surrogate modelling in the geosciences." version: 1.0.0 doi: 10.5281/zenodo.10479132 date-released: 2024-01-10 url: "https://github.com/cerea-daml/tdma-practical-session"
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Dependencies
- tensorflow *