Code for our 2022 ICML paper "Distinguishing rule and exemplar-based generalization in learning systems." To cite the work that this code is associated with, use:
@inproceedings{dasgupta20222distinguishing,
title={Distinguishing rule and exemplar-based generalization in learning systems},
author={Dasgupta, Ishita and Grant, Erin and Griffiths, Tom},
booktitle={Proceedings of the 39th International Conference on Machine Learning},
pages={4816--4830},
year={2022},
editor={Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
volume={162},
series={Proceedings of Machine Learning Research},
month={17--23 Jul},
publisher={PMLR},
url={https://proceedings.mlr.press/v162/dasgupta22b.html},
}
Install the package, then run a command such as the following:
python scripts/main.py --gin_config='configs/static/celeba.gin'
Also see the analysis notebooks in analyses/
.
To install via Conda, do:
git clone git@github.com:eringrant/icml-2022-rules-vs-exemplars
cd icml-2022-rules-vs-exemplars
conda env create --file environment.yml
The Conda environment can then be activated via
conda activate rules-vs-exemplars
To install via pip, do:
git clone git@github.com:eringrant/icml-2022-rules-vs-exemplars
cd icml-2022-rules-vs-exemplars
pip install -e .