Each folder of this codebase corresponds to a set of experiments in the main paper.

For a public-facing, up-to-date version of this code please visit github.com/ronakrm/demd/.

# Efficient Computation of d-Dimensional Earth Mover's Distance
This repository contains the implementation and experiments for ICLR 2023: Efficient Discrete Multi Marginal Optimal Transport Regularization.
Each folder corresponds to a unique experiment in the main paper, and each folder contains the corresponding version of our DEMD codebase.
For current plug-and-play, check out the `demd` folder within, and particularly `demdLoss.py`, `DEMDLayer.py`, and `demdFunc.py`.

## Reference
```
@inproceedings{
mehta2023efficient,
title={Efficient Discrete Multi Marginal Optimal Transport Regularization},
author={Ronak Mehta and Jeffery Kline and Vishnu Suresh Lokhande and Glenn Fung and Vikas Singh},
booktitle={International Conference on Learning Representations},
year={2023},
url={https://openreview.net/forum?id=R98ZfMt-jE}
}
```
