Open AccessData-driven learning of nonlocal physics from high-fidelity synthetic data.
Author(s) -
Mamikon Gulian
Publication year - 2021
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2172/1854073
Subject(s) - homogenization (climate) , kernel (algebra) , fidelity , mathematics , operator (biology) , workflow , statistical physics , computer science , mathematical optimization , physics , pure mathematics , biodiversity , ecology , telecommunications , biochemistry , chemistry , repressor , database , transcription factor , gene , biology
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