jaxhps: An elliptic PDE solver built with machine learning in mind
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| Autori principali: | , , , |
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901553168777216 |
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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 |