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pypi.org : pysipfenn

Python toolset for Structure-Informed Property and Feature Engineering with Neural Networks. It offers unique advantages through (1) effortless extensibility, (2) optimizations for ordered, dilute, and random atomic configurations, and (3) automated model tuning.

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purl: pkg:pypi/pysipfenn
Keywords: computational-materials-science, computational-thermodynamics, featurization, materials, materials-genome, materials-informatics
License: LGPL-2.1,GPL-2.0+
Latest release: about 1 month ago
First release: over 1 year ago
Downloads: 135 last month
Stars: 16 on GitHub
Forks: 3 on GitHub
Total Commits: 145
Committers: 4
Average commits per author: 36.25
Development Distribution Score (DDS): 0.034
More commit stats: commits.ecosyste.ms
See more repository details: repos.ecosyste.ms
Last synced: 11 days ago

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