Identity
- Type
- university
- Country label
- not in the notes
- HQ country
- not in the notes
- Founding country
- not in the notes
- Parent
- not in the notes
- Parent country
- not in the notes
- Country basis
- the research notes
Where this comes from
Convention D1: a dual label, HQ first, when the HQ, founding or parent country differ.
Models by Class
Models
ModelClassOpennessParametersReleased
PET-OAM-XLmaterials10 Jan 2026Links
OrganisationEPFLuniversity
EPFLuniversityUse Casesnone recorded
Who Runs Itnone recorded
Scores
| Benchmark | Model | Score | Who ran it | Setting |
|---|---|---|---|---|
| Matbench Discovery | PET-OAM-XL | 0.119 kSRME | maintainer-run | lower is better |
| Matbench Discovery | PET-OAM-XL | 0.898 CPS | maintainer-run | |
| Matbench Discovery | PET-OAM-XL | 0.924 F1 | maintainer-run |
Where this comes from
Every recorded score of this organisation's models, with who ran it. Scores from different settings are not directly comparable.
Sources
- A new reference model for machine learning-driven materials discovery actu.epfl.ch https://actu.epfl.ch/news/a-new-reference-model-for-machine-learning-driven
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "EPFL", https://aurion.semai.id/organisations/epfl/, records of October 2026.