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AIM 2025: Equivariance Tutorial

Getting started

The code for the tutorial is in this GitHub repository; to get it locally you need to have git installed (Git for Windows).

The tutorial is implemented in Python. Miniconda is a package manager that allows you to get Python and install all necessary packages.

Once you have both installed, navigate to the directory in which you want to save this tutorial and open it in the miniconda prompt. There, execute the command

git clone https://github.com/finnsherry/EquivarianceTutorial

Next, navigate into the downloaded repository using

cd EquivarianceTutorial

Now, create and activate a conda environment

conda create -n equivariance python=3.13
conda activate equivariance

You can now install all necessary packages:

pip install requirements.txt

The tutorial is a jupyter notebook, you can find it by executing

jupyter lab

Alternatively, you can open it in code editors such as Visual Studio Code.

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Tutorial about equivariance for AIM's fourth PhD networking event

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