Code for stochastic area metric : binary search for speed

de Angelis, M. and Sunny, J. (2022) Code for stochastic area metric : binary search for speed. GitHub. (https://doi.org/10.5281/ZENODO.6366288)

Abstract

This repository contains Python scientific code for computing efficiently the area metric, a.k.a. 1-Wasserstein distance, between tabular samples. The code is optimized by running Numpy under the hood, thus is as vectorized as possible. A basic Matlab version is also present in this repository.

ORCID iDs

de Angelis, M. ORCID: https://orcid.org/0000-0001-8851-023X

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• Item metadata

  Item type:	Other
  ID code:	83060
  Dates:	Date Event 17 March 2022 Published
  Subjects:	Technology > Engineering (General). Civil engineering (General)
  Department:	Faculty of Engineering > Civil and Environmental Engineering
  Depositing user:	Pure Administrator
  Date deposited:	03 Nov 2022 12:48
  Last modified:	11 Nov 2024 16:10
  URI:	https://strathprints.strath.ac.uk/id/eprint/83060