Saved in:
Bibliographic Details
Main Author: Kaushal, Neerav
Format: Recurso digital
Language:
Published: Zenodo 2025
Online Access:https://doi.org/10.5281/zenodo.18026531
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866902336032473088
author Kaushal, Neerav
author_facet Kaushal, Neerav
contents <p>This repository contains data and pretrained model checkpoint used in the nuGAN (neutrino GAN) paper.</p> <p>Data:<br>- scaled_density_contrast_maps.npy: 2D density maps of shape (15000,256,256). Maps correpsonding to neutrino masses 0.0, 0.1, 0.4, 0.8, and 12.2 can be chosen by indices [:3000], [3000:6000], [6000:9000], [9000,12000], and [12000:] respectively.<br>- neutrino_masses.npy: corresponding neutrino masses of shape (15000,). Same indexing for as above.</p> <p>Model:<br>- Trained nuGAN checkpoint state dict</p> <p> </p> <p>These resources are provided without restrictions.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18026531
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle νGAN: A Deep Learning Emulator for Cosmic Web Simulations with Massive Neutrinos
Kaushal, Neerav
<p>This repository contains data and pretrained model checkpoint used in the nuGAN (neutrino GAN) paper.</p> <p>Data:<br>- scaled_density_contrast_maps.npy: 2D density maps of shape (15000,256,256). Maps correpsonding to neutrino masses 0.0, 0.1, 0.4, 0.8, and 12.2 can be chosen by indices [:3000], [3000:6000], [6000:9000], [9000,12000], and [12000:] respectively.<br>- neutrino_masses.npy: corresponding neutrino masses of shape (15000,). Same indexing for as above.</p> <p>Model:<br>- Trained nuGAN checkpoint state dict</p> <p> </p> <p>These resources are provided without restrictions.</p>
title νGAN: A Deep Learning Emulator for Cosmic Web Simulations with Massive Neutrinos
url https://doi.org/10.5281/zenodo.18026531