Lie Algebra Convolutional Network (L-conv) implementation

Paper: Automatic Symmetry Discovery with Lie Algebra Convolutional Network Nima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu NeurIPS 2021
(find updated versions on arxiv)

Contents

A simple implementation of the L-conv layer in PyTorch (>=1.8) can be found in src/lconv.py. The L-conv layer acts similar to a graph convlutional layer (GCN), so prepare your input in a similar fashion (e.g. flatten the spatial dimensions). The input should have shape (batch, channels, #nodes) (e.g. on an image, # nodes = # pixels)
This repository also contains code and notebooks for the experiemnts in the paper (appendix C and D) under paper-code. Most experiments in appendix D use an older (but identical) implementation in Tensoflow (>=2.1). Comparison with LieConv in appendix D requires the LieConv packages.

TBA soon:

Exmaples of uses will be added soon.