This study presents a data-efficient foundation model for porous materials, developed using expert-guided supervised learning. The approach aims to address the challenge of data scarcity in material artificial intelligence. The researchers constructed a supervised learning pipeline that incorporates expert knowledge to enhance the model's performance, potentially overcoming the limitations of traditional data-driven approaches.
A data-efficient foundation model for porous materials based on expert-guided supervised learning
Informational, non-clinical synthesis informed by published research. Not a clinical guideline or medical advice. May contain errors or editorial interpretation. Consult the original source and your physician.
