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Literature Overview: Machine Learning for Cryospheric Sciences

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Machine Learning for the Cryosphere: A Literature Overview

This is an open-source collection of relevant literature within ML for Cryospheric Sciences.

Please navigate to the project page. Here you can find a structured overview of our current state of literature review.

Everything else in this README refers to that project page.

How to add a publication

TLDR: Open an issue, I'll add you, you can add your publication. Do not add new items to the colored items.

  1. Open an issue naming that you want to be added to the project/repo. State how you want to contribute. I will add you so you get write access.
  2. Add a publication you have found. Please add as many of the visible fields as possible.
  • The field status: Use the tag "newly added" here, so we know we have to review it.
  • The field assignee: Put your own github user handle here. This way we know who added that item. We will assign a reviewer to it.
  • The field cryo area: This one is important. Please choose one of the areas that are already there. Don't add a new one - open an issue if you think there should be another area added here.
  • The field task: Same as for "cryo area"
  • The field type of data: If you do not find it in the drop-down menu, just add the type of data used here. Keep it general though. Instead of saying 'SNOWPACK data', use something like: 'snow model', such that other snowpack models are included in that area as well.
  1. You are done - thank you for contributing! If you are contributing significantly to this project we will reach out to you and speak about how to credit your work (e.g. acknowledgements or authorship).

How to gain insights

You can download the data and perform your data analysis on it. You can look at the charts (e.g. number of counts for each cryo area)

How to cite us

Please cite us if you use our work. There will be a literature overview publication that can be cited.

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