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kpoints-goldilocks-ALIGNNd
STFC-SCD/kpoints-goldilocks-ALIGNNd
kpoints-goldilocks-ALIGNNd is a machine learning model from STFC-SCD. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-4.0.
These are ALIGNNd models trained with standard quantile loss to predict the kpoints-density for different quantiles. For each quantile top 3 (quantile loss minimal on the validation set) checkpoints are recorded.
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Updated Dec 8, 2025
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- License
- cc-by-4.0
- Access
- Public
- Created
- Dec 8, 2025
- Updated
- Dec 8, 2025
- SHA
- ec7eb473
Model card
From the Hugging Face model README
These are ALIGNNd models trained with standard quantile loss to predict the kpoints-density for different quantiles. For each quantile top 3 (quantile loss minimal on the validation set) checkpoints are recorded.
The implementation of ALIGNNd model can be found here https://github.com/stfc/goldilocks_kpoints. For these checkpoints input features are embeddings/atom_init_with_sssp_cutoffs.json, additional features are composition, structure, lattice, and metallicity embeddings
Performance of the model trained for 0.5 quantile is:
MAE: 0.069
MAPE: 0.189
MSE: 0.0097
R2 score: 0.697
Spearman_corr: 0.866
Kendall_corr: 0.677
Associated repositories are:
- License
- cc-by-4.0
- Created
- Dec 8, 2025
- Updated
- Dec 8, 2025