The FIX Benchmark: Extracting Features Interpretable to eXperts
Paper
• 2409.13684 • Published
Search is not available for this dataset
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Dataset Structure
This dataset contains clean simulated weak lensing maps without noise.
Data Fields
- input: 4D tensor of shape (N, 1, 66, 66) containing weak lensing maps, N=number of examples.
- label: 2D array of shape (N, 2) containing the label for cosmological parameters $\Omega_m$ and $\sigma_8$ for each examples.
Data Splits
- train: 90,000 examples
- validation: 10,000 examples
- test: 10,000 examples
Usage
from datasets import load_dataset
dataset = load_dataset('BrachioLab/massmaps-cosmogrid-100k')
Citation
Please cite FIX and CosmogridV1
@misc{jin2024fix,
title={The FIX Benchmark: Extracting Features Interpretable to eXperts},
author={Helen Jin and Shreya Havaldar and Chaehyeon Kim and Anton Xue and Weiqiu You and Helen Qu and Marco Gatti and Daniel A Hashimoto and Bhuvnesh Jain and Amin Madani and Masao Sako and Lyle Ungar and Eric Wong},
year={2024},
eprint={2409.13684},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
@article{Kacprzak_2023,
title={CosmoGridV1: a simulated 𝗐CDM theory prediction for map-level cosmological inference},
volume={2023},
ISSN={1475-7516},
url={http://dx.doi.org/10.1088/1475-7516/2023/02/050},
DOI={10.1088/1475-7516/2023/02/050},
number={02},
journal={Journal of Cosmology and Astroparticle Physics},
publisher={IOP Publishing},
author={Kacprzak, Tomasz and Fluri, Janis and Schneider, Aurel and Refregier, Alexandre and Stadel, Joachim},
year={2023},
month=feb, pages={050} }
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