Published February 12, 2024 | Version v1
Dataset Open

An operator learning perspective on parameter-to-observable maps

  • 1. ROR icon Peking University
  • 2. ROR icon California Institute of Technology

Description

This repository contains the datasets corresponding to the three benchmark problems for the Fourier Neural Mappings scientific machine learning architectures. The first file is the data for the advection-diffusion problem, the second for the airfoil problem, and the third for the elliptic homogenization materials problem. The code associated with these data may be found at https://github.com/nickhnelsen/fourier-neural-mappings

Files

advection_diffusion.zip
Files (7.1 GB)
Name Size
md5:4697bde4c0218f65e791c04f17a8bd57
670.3 MB Preview Download
md5:d3e6f5e07bfff7034bb01b99faae16f7
1.4 GB Preview Download
md5:dac3b605e36911af2ea4d37394a7308e
5.1 GB Preview Download

Additional details

Created:
February 12, 2024
Modified:
June 6, 2024