README.md

Latent Space Symmetry Discovery (LaLiGAN)

Code for our ICML 2024 paper, Latent Space Symmetry Discovery.

Setup the Environment

conda create -n laligan python=3.9
conda deactivate
conda activate laligan

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip3 install scipy==1.10.1
pip3 install tqdm==4.64.1

cd src

Setup Datasets

Reaction-Diffusion System

The system is simulated with the Matlab scripts provided in SINDy Autoencoders.

Running the script reaction_diffusion.m should produce the data file reaction_diffusion.mat. Then, place it under ./data in this repository.

Alternatively, download the data from this link.

Rotating Object

Generate the renderings of a bookshelf with different orientations:

python data_utils/rot_obj.py --num_samples 10000 --name train
python data_utils/rot_obj.py --num_samples 100 --name val
python data_utils/rot_obj.py --num_samples 100 --name test

Experiments

Reaction-Diffusion System

LaLiGAN Symmetry discovery in 2D latent space:

python main.py --config rd

LaLiGAN Symmetry discovery in 3D latent space:

python main.py --config rd_3d

SINDy equation discovery in the LaLiGAN 2D latent space:

python main_sindy.py --config rd_sindy

SINDy equation discovery in the LaLiGAN 3D latent space:

python main_sindy.py --config rd_sindy_3d

SINDy Autoencoder equation discovery in the 3D latent space:

python main.py --config rd_sindyonly

Nonlinear Pendulum

LaLiGAN Symmetry discovery for nonlinear pendulum:

python main.py --config pendulum

(Baseline) LieGAN symmetry discovery for nonlinear pendulum:

python main.py --config pendulum_liegan

SINDy equation discovery in the LaLiGAN latent space:

python main_sindy.py --config pendulum_sindy

SINDy Autoencoder equation discovery:

python main.py --config pendulum_sindyae

SINDy equation discovery w/o autoencoder:

python main.py --config pendulum_sindyonly

Lotka-Volterra Equations

LaLiGAN Symmetry discovery for Lotka-Volterra system:

python main.py --config lv

(Baseline) LieGAN symmetry discovery Lotka-Volterra system:

python main.py --config lv_liegan

SINDy equation discovery in the LaLiGAN latent space:

python main_sindy.py --config lv_sindy

SINDy Autoencoder equation discovery:

python main.py --config lv_sindyae

SINDy equation discovery w/o autoencoder:

python main.py --config lv_sindyonly

Double Bump World

Learning $\mathrm{SO}(2) \times \mathrm{SO}(2)$ equivariant representation:

python main.py --config double_bump

Rotating Object

Learning $\mathrm{SO}(3)$ equivariant representation:

python main.py --config rs

Cite

@inproceedings{yang24latent,
  title     =  {Latent Space Symmetry Discovery},
  author    =  {Yang, Jianke and Dehmamy, Nima and Walters, Robin and Yu, Rose},
  booktitle =  {Proceedings of the 41st International Conference on Machine Learning},
  pages     =  {56047--56070},
  year      =  {2024},
  volume    =  {235},
  series    =  {Proceedings of Machine Learning Research},
  publisher =  {PMLR},
  url       =  {https://proceedings.mlr.press/v235/yang24g.html},
}