How to Train a Shallow Ensemble
), and a model tetrapeptide (Ac-Ala3-NHMe), establishing practical guidelines for reliable uncertainty quantification in atomistic machine learning.
Authors
- Johannes Kästner (ORCID: https://orcid.org/0000-0001-6178-7669)
- Matthias Kellner (ORCID: https://orcid.org/0009-0008-3849-7813)
- Moritz Schäfer
- Michele Ceriotti (ORCID: https://orcid.org/0000-0003-2571-2832)
Institutions
- University of Stuttgart (DE)
- Centre des Matériaux (FR)
- École Polytechnique Fédérale de Lausanne (CH)
Publication Details
- Journal
- Journal of Chemical Theory and Computation
- Published
- 2026-05-08
- DOI
- https://doi.org/10.1021/acs.jctc.6c00310
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Deutsche Forschungsgemeinschaft
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Stuttgart Center for Simulation Science, Universität Stuttgart