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Main Authors: Melia, Owen, Fortunato, Daniel, Hoskins, Jeremy, Willett, Rebecca
Format: Recurso digital
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Published: Zenodo 2025
Online Access:https://doi.org/10.5281/zenodo.17610335
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author Melia, Owen
Fortunato, Daniel
Hoskins, Jeremy
Willett, Rebecca
author_facet Melia, Owen
Fortunato, Daniel
Hoskins, Jeremy
Willett, Rebecca
contents <p>This is an archival copy of the <code>jaxhps</code> software package, at version <code>v0.2</code>. <code>jaxhps</code> is a Python package, written in JAX, which implements GPU-compatible direct solvers for variable coefficient linear elliptic PDEs. The source repository for the <code>jaxhps</code> project is available at <a href="https://github.com/meliao/jaxhps">https://github.com/meliao/jaxhps</a>. </p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17610335
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle jaxhps: An elliptic PDE solver built with machine learning in mind
Melia, Owen
Fortunato, Daniel
Hoskins, Jeremy
Willett, Rebecca
<p>This is an archival copy of the <code>jaxhps</code> software package, at version <code>v0.2</code>. <code>jaxhps</code> is a Python package, written in JAX, which implements GPU-compatible direct solvers for variable coefficient linear elliptic PDEs. The source repository for the <code>jaxhps</code> project is available at <a href="https://github.com/meliao/jaxhps">https://github.com/meliao/jaxhps</a>. </p>
title jaxhps: An elliptic PDE solver built with machine learning in mind
url https://doi.org/10.5281/zenodo.17610335