lollcat/ecnf-baseline-neurips-2023

Equivariant continuous normalizing flow trained via flow matching

ecnf

Flow matching with vector field parameterized by SE(3) GNN for the paper "SE(3) Equivariant Augmented Coupling Flows".

Running experiments

python examples/dw4.py
python examples/lj13.py
python examples/qm9.py

We use wandb for logging - if you use wandb then adjust the config inside examples/config/{problem_name}.yaml appropriately. Additionally there is a pandas/list logger if you don't use wandb. Feel free to contact us if you would like any help running this code.

Useful links

• SE(3) Equivariant Augmented Coupling Flows repo
• Flow Matching for Generative Modeling
• Diffrax: SDEs and ODEs in JAX

Citation

@article{
midgley2023se3couplingflow,
title={SE(3) Equivariant Augmented Coupling Flows},
author={Laurence Illing Midgley and Vincent Stimper and Javier Antor{\'a}n and Emile Mathieu and Bernhard Sch{\"o}lkopf and Jos{\'e} Miguel Hern{\'a}ndez-Lobato},,
journal={arXiv preprint arXiv:2308.10364}
year={2023},
}