WMD-group/ElementEmbeddings

Python package to interact with high-dimensional representations of the chemical elements

43
/ 100
Emerging

This tool helps materials scientists understand and compare how different computational models 'see' chemical elements. It takes high-dimensional data representing chemical elements and processes them to reveal similarities and differences between various elemental or ionic embedding schemes. The output helps researchers interpret machine learning models and validate their underlying representations of elements.

Use this if you are a materials scientist or researcher who works with machine learning models and needs to evaluate or compare different ways that chemical elements are numerically represented (embeddings).

Not ideal if you are looking for a tool to train new machine learning models from scratch or to generate new elemental embeddings.

materials-science computational-chemistry materials-informatics elemental-representation embedding-analysis
No Package No Dependents
Maintenance 10 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 9 / 25

How are scores calculated?

Stars

51

Forks

4

Language

Python

License

MIT

Last pushed

Feb 23, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/WMD-group/ElementEmbeddings"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.