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When Machine Learning Meets Multiscale Modeling in Chemical Reactions
[article]
2020
arXiv
pre-print
Preserved Fulltext
Due to the intrinsic complexity and nonlinearity of chemical reactions, direct applications of traditional machine learning algorithms may face with many difficulties. In this study, through two concrete examples with biological background, we illustrate how the key ideas of multiscale modeling can help to reduce the computational cost of machine learning a lot, as well as how machine learning algorithms perform model reduction automatically in a time-scale separated system. Our study
arXiv:2006.00700v1
fatcat:r7ccjwjdzfc6xlhtnczggf5wri