TPSA-augmented QM9 GNN

This project leverages a reproducible devcontainer environment, making it easy to set up and run on any machine with Docker and Visual Studio Code (or another compatible editor). By comparing three state-of-the-art GNN architectures (GCN, GAT, and GIN), the project provides insights into their relative performance in a regression task.

Molecular Graphs QM9 Graph-level Regression GNN