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Deep learning and variational inversion to quantify and attribute climate change (CIRC23)

Continuous integration badge Binder doi notebook review

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How to run

Running locally

You may also download the notebook from GitHub to run it locally:

  1. Open your terminal

  2. Check your conda install with conda --version. If you don't have conda, install it by following these instructions (see here)

  3. Clone the repository

    git clone https://github.com/eds-book-gallery/93463cac-471a-469d-ad52-0514fd9b67f2.git
  4. Move into the cloned repository

    cd 93463cac-471a-469d-ad52-0514fd9b67f2
  5. Create and activate your environment from the .binder/environment.yml file

    conda env create -f .binder/environment.yml
    conda activate 93463cac-471a-469d-ad52-0514fd9b67f2
  6. Launch the jupyter interface of your preference, notebook, jupyter notebook or lab jupyter lab

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Detection and attribution of climate change using deep learning

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