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Graph learning

The objective of these notebooks is to present different analysis methods for graph. They are implementations of algorithms presented on the UTC master lecture on graph learning (AOS6) taught by Jean-Benoist Leger. It is not a global project but more a compilation of homeworks.

Table of contents

In the first notebook, we will present the different methods of clustering. In the second notebook, we will present the different methods of radom graph generation.

Installation

To run this notebook, a environment.yml for setting an conda env with python12.

conda env create -f environment.yml

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