329 citations · 663 across the 15 of their papers we have counts for
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cs.NE2021
Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE)
Yuntian Chen, Yingtao Luo, Qiang Liu +2
Partial differential equations (PDEs) are concise and understandable representations of domain knowledge, which are essential for deepening our understanding of physical processes…
cs.NE2020
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm
Hao Xu, Haibin Chang, Dongxiao Zhang
Data-driven methods have recently been developed to discover underlying partial differential equations (PDEs) of physical problems. However, for these methods, a complete candidate…