Code for D-CODE: Discovering Closed-form ODEs from Observed Trajectories (ICLR 2022).
Clone this repository and all submodules (e.g. using git clone --recursive).
Python 3.6+ is recommended. Install dependencies as per requirements.txt.
Shell scripts to replicate the experiments can be found in run_all.sh.
To run all the synthetic data experiments:
$ bash run_all.shYou may also run the experiment steps individually, see run_all.sh.
To then produce the figures, run the Jupyter notebooks Result Summary.ipynb, Fig3.ipynb, Fig5.ipynb, rebuttal.ipynb.
If you use this code, please cite the associated paper:
@inproceedings{NEURIPS2021,
author = {Qian, Zhaozhi and Kacprzyk, Krzysztof and van der Schaar, Mihaela},
booktitle = {International Conference on Learning Representations},
title = {D-CODE: Discovering Closed-form ODEs from Observed Trajectories},
url = {https://openreview.net/pdf?id=wENMvIsxNN},
volume = {10},
year = {2022}
}