Skip to main content

Reference implentation of the Automated Small Symmetric Structure Training method.

Project description

DOI Documentation Status

ASSYST or Automated Small SYmmetric Structure Training

A minimal reference implementation of ASSYST method to generate transferable training data for machine learning potentials, see also the corresponding paper.

Please use the following citation when referencing the method in your work.

@article{poul2025automated,
  title={Automated generation of structure datasets for machine learning potentials and alloys},
  volume={11},
  DOI={10.1038/s41524-025-01669-4},
  number={1},
  journal={npj Computational Materials},
  author={Poul, Marvin and Huber, Liam and Neugebauer, J\"org},
  year={2025},
  month={Jun}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

assyst-0.6.1.tar.gz (125.4 kB view details)

Uploaded Source

File details

Details for the file assyst-0.6.1.tar.gz.

File metadata

  • Download URL: assyst-0.6.1.tar.gz
  • Upload date:
  • Size: 125.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.8

File hashes

Hashes for assyst-0.6.1.tar.gz
Algorithm Hash digest
SHA256 2e6e56d1c034fe30bee70c5c174c37e9f2f0dc69dbe387d9a04fd9b60e03752f
MD5 738be09da26d1210e0ea7a27500bd77c
BLAKE2b-256 3c091111e14526f5c57cdabcb3c73154618bb45bbe69ac94ff78236337e95ed8

See more details on using hashes here.

Provenance

The following attestation bundles were made for assyst-0.6.1.tar.gz:

Publisher: pypi-publish.yml on eisenforschung/assyst

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page