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

Related tags

Deep Learningdeep-neural-networksdeep-learningpytorchneural-networkshomomoleculesgraph-neural-networksgnnequivarianceqm9egnn
Overview

Simple implementation of Equivariant GNN

Open In Colab

  • A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction.
  • Just 50 lines of code;
  • The implementation is based on pure PyTorch & Numpy, it has no external packages (like PyTorch-geometric).
  • Closely matches the Mean Absolute Error reported in the paper.

Owner
Arsenii Senya Ashukha
Research scientist at @SamsungLabs AI Center Moscow @bayesgroup
Arsenii Senya Ashukha
GitHub Repository
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