Prediction of chemical reaction yields with large-scale multi-view pre-training
Runhan Shi, Gufeng Yu, Xiaohong Huo, Yang Yang
DOI: 10.1186/s13321-024-00815-2
Journal: Journal of Cheminformatics
The ReaMVP framework improves the generalization capability of machine learning models for predicting chemical reaction yields by integrating sequential and geometric views and leveraging self-supervised learning techniques with a two-stage pre-training strategy, which achieves state-of-the-art performance on benchmark datasets.
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Journal Info
Journals:
ISSN 1758-2946
Quartile
Category | Quartile |
COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | 1 |
Quartile(CN)
Category | Quartile |
化学 | 2 |
化学, 化学综合 | 2 |
化学, 计算机信息系统 | 2 |
化学, 计算机跨学科应用 | 3 |