Noether Networks: meta-learning useful conserved quantities

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Deep Learning noether-networks
Overview

Noether Networks: meta-learning useful conserved quantities

This repository contains the code necessary to reproduce experiments from "Noether Networks: meta-learning useful conserved quantities." Noether Networks meta-learn inductive biases in the form of useful conserved quantities. For details on the method, check out our NeurIPS 2021 paper, linked on our project website.

For instructions on how to train and evaluate a Noether Network for video prediction, check out video_prediction/README.md.

Citation

If this work is useful to you, please cite our paper:

@inproceedings{
alet2021noether,
title={Noether Networks: meta-learning useful conserved quantities},
author={Ferran Alet and Dylan Doblar and Allan Zhou and Joshua B. Tenenbaum and Kenji Kawaguchi and Chelsea Finn},
booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
year={2021},
url={https://openreview.net/forum?id=_NOwVKCmSo}
}
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Comments
  • [Proposal/Feature Request] Drop constraint in packages which are to be installed from Github

    [Proposal/Feature Request] Drop constraint in packages which are to be installed from Github

    While trying to create a virtual environment I ran into issues multiple times while installing lpips-pytorch and lpips-tensorflow from their specific commit hash. viz.

    https://github.com/dylandoblar/noether-networks/blob/c7a65a2dd168a92a32458f82eb263157b12f4793/video_prediction/requirements.txt#L42-L43

    Removing the commit hash worked just as well for training purposes. i.e.

    git+https://github.com/S-aiueo32/lpips-pytorch.git
git+https://github.com/alexlee-gk/lpips-tensorflow.git

    Therefore I propose that version constraints be dropped for lpips-pytorch, lpips-tensorflow and RoboNet.

    PS: Congratulations to the authors for the paper getting into NeurIPS'21 🤩

    opened by SauravMaheshkar 0
Owner
Dylan Doblar
Dylan Doblar
GitHub
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