metadata
license: mit
dataset_info:
features:
- name: kappa
dtype:
array3_d:
shape:
- 101
- 1424
- 176
dtype: float16
- name: theta
dtype:
array2_d:
shape:
- 101
- 5
dtype: float32
splits:
- name: train
num_bytes: 13108270080
num_examples: 256
download_size: 6934979115
dataset_size: 13108270080
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
FAIR Universe - NeurIPS 2025 Weak Lensing Uncertainty Challenge
This dataset is a HF mirror of the official challenge training data for this challenge:
https://www.codabench.org/competitions/8934/
To ease the split along the nuisance parameter axis, the dataset challenge has been reordered as
ncosmo, np, ... -> np, ncosmo, ...
To get started:
import datasets
dset = datasets.load_dataset("cosmostat/neurips-wl-challenge")
dset = dset.with_format('torch')
example = dset['train'][0]