Skip to main content

Reference implentation of the Automated Small Symmetric Structure Training method.

Project description

DOI Documentation Status codecov

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-0.8.1.tar.gz (130.1 kB view details)

Uploaded Source

File details

Details for the file assyst-0.8.1.tar.gz.

File metadata

  • Download URL: assyst-0.8.1.tar.gz
  • Upload date:
  • Size: 130.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.8

File hashes

Hashes for assyst-0.8.1.tar.gz
Algorithm Hash digest
SHA256 434769630e750ea66733eb7615a69492ed916dd90b0f6624cfd52a07ab218c58
MD5 612aef709b92635a94513c21e7b567f7
BLAKE2b-256 27bf2c456f503f532975fd2e7f4b822bf4874cba807e10607ca085542f86c268

See more details on using hashes here.

Provenance

The following attestation bundles were made for assyst-0.8.1.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