A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks

A Python package for data-mining the QM9 dataset

Predicting properties of small molecules using MPNN on QM9 dataset

Graph Neural Network creation module, implemented in Tensorflow 2 with examples using the module and the iGNNition library for fast GNN prototyping.

A Variational Autoencoder in Google Colab to generate and visualize novel molecular structures for potential drug discovery applications, using the QM9 dataset and SMILES representation.

A update QM9 benchmark, update form the recent articles