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Machine Learning and Computational Mathematics
In this article, we try to address the following two very important questions: (1) How machine learning has already impacted and will further impact computational mathematics, scientific computing and computational science?
DeePKS: a comprehensive data-driven approach towards chemically accurate density functional theory
We propose a general machine learning-based framework for building an accurate and widely-applicable energy functional within the framework of generalized Kohn-Sham density functional theory.
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