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fyp-active-learning-models
gcnwm/fyp-active-learning-models
fyp-active-learning-models is a machine learning model from gcnwm. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This supplementary model/ folder stores a curated export of the strongest final-iteration checkpoints from the MACE and NequIP active-learning study on rMD17 ethanol. Each bundle is selected by the best final forces M…
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Updated May 16, 2026
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- Access
- Public
- Created
- Apr 16, 2026
- Updated
- May 16, 2026
- SHA
- 19f29cb6
Model card
From the Hugging Face model README
Curated FYP Active-Learning Checkpoints
This supplementary model/ folder stores a curated export of the strongest
final-iteration checkpoints from the MACE and NequIP active-learning study on
rMD17 ethanol. Each bundle is selected by the best final forces MAE across the
three repeated experiment seeds for its architecture/strategy family.
Included bundles
| Bundle | Architecture | Strategy | Selected seed | Final forces MAE (meV/Å) | Final energy MAE (meV) | Files |
|---|---|---|---|---|---|---|
| mace-random | MACE | RANDOM | 1 | 9.45 | 1.79 | 2 |
| mace-qbc | MACE | QBC | 3 | 8.61 | 1.69 | 8 |
| nequip-random | NequIP | RANDOM | 2 | 10.66 | 4.24 | 7 |
| nequip-qbc | NequIP | QBC | 3 | 9.53 | 6.52 | 21 |
| mace-passive | MACE | Passive control | 3 | 10.19 | 2.05 | 3 |
| nequip-passive | NequIP | Passive control | 1 | 10.13 | 2.55 | 2 |
Notes
mace-qbc/contains the full four-member committee for the selected QBC seed.nequip-qbc/contains one raw/package/compiled triplet per selected committee member.- Per-bundle
metadata.jsonfiles record the selected seed, final metrics, and original relative source paths from the thesis workspace.
Passive controls
The passive bundles are same-budget 550-label controls from the frozen v4 split. They are included to support the thesis comparison against active QBC/random methods; they are not active-learning acquisition runs.
- Created
- Apr 16, 2026
- Updated
- May 16, 2026