SynCoTrain: a dual classifier PU-learning framework for synthesizability prediction
SynCoTrain is a PU-learning framework using dual GNN classifiers to predict material synthesizability. It leverages co-training to mitigate model bias and enhance generalizability.
Authors
- Philipp Benner (ORCID: https://orcid.org/0000-0002-0912-8137)
- Janine George (ORCID: https://orcid.org/0000-0001-8907-0336)
- Sasan Amariamir
Institutions
- Federal Institute For Materials Research and Testing (DE)
- Friedrich Schiller University Jena (DE)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d4dd00394b
- Citations
- 4
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 2.07