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Learning about GNN

dependencies

This repository contains some tutorials and experiments to learn about Graph Neural Networks, using PyTorch Geometric as the main framework. Currently, only one learning task is covered:

  • graph classification

Project structure

Each folder under experiments contains a main.py file which runs the corresponding experiment. The main file imports classes from:

  • src/<experiment>/utils for generic data loading & preprocessing
  • src/<experiment>/datasets for functions specific to a certain dataset
  • src/<experiment>/models for model initialization, training & inference