metadata
license: bsd-3-clause
language:
- en
tags:
- atomistic-machine-learning
- materials-science
ecumetric
This repository contains the ecumetric model and sketch-map projector which were used in MAD-CORE.
The ecumetric model (ecumetric_model.pt) provides descriptors used to construct the
MAD-CORE hierarchy. The model uses the SPACE architecture of
metatrain. Its per-atom feature output is
pooled into one 512-dimensional vector per structure, with concatenation of the mean and
the standard deviation over atoms. Distances between these vectors, after scaling,
define the ecumetric metric.
The ecumetric explorer model (ecumetric_explorer.pt) maps the ecumetric descriptors to
eight-dimensional sketch-map coordinates for exploration and visualization.
For re-exporting, see reproduce/README.md.
Exploring a dataset with chemiscope
import ase.io
import chemiscope
structures = ase.io.read("structures.xyz", ":")
chemiscope.explore(structures, featurizer="ecumetric-1.0")
Citation
- MAD-CORE: Sofiia Chorna, Cesare Malosso, Jonathan Schmidt, Michele Ceriotti, Hierarchical universal open structure dataset for atomistic modeling, https://arxiv.org/abs/2610.21771
- SPACE architecture: https://arxiv.org/abs/2610.10830
- sketch-map: https://doi.org/10.1073/pnas.1108486108