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

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Deep Learning deep-neural-networks deep-learning pytorch neural-networks homo molecules graph-neural-networks gnn equivariance qm9 egnn
Overview

Simple implementation of Equivariant GNN

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  • 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.

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Comments
  • Figure generation

    Figure generation

    Hi, I try to generate the figure as like yours, but I couldn't do that. Would you like to tell me how can plot figure like yours, can you share the code for that please if available?

    opened by jahidhasanlinix 1
  • second cell of the notebook

    second cell of the notebook

    Hi, I'm testing your notebook, it looks great! I would suggest adding a % symbol at the start of the line to change directory in the second cell, like this: %cd simple-equivariant-gnn

    opened by napoles-uach 1
Owner
Arsenii Senya Ashukha
Research scientist at @SamsungLabs AI Center Moscow @bayesgroup
Arsenii Senya Ashukha
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