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

Last update: Dec 23, 2022

Overview

Simple implementation of Equivariant GNN

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

GitHub Repository

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

Related tags

Overview

Simple implementation of Equivariant GNN

Owner

Arsenii Senya Ashukha

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