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most citedA unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions

100 citations · 184 across the 9 of their papers we have counts for

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cs.LG2022★ 6 cited

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks

Shibo Li, Michael Penwarden, Yiming Xu +4

Physics-informed neural networks (PINNs) are emerging as popular mesh-free solvers for partial differential equations (PDEs). Recent extensions decompose the domain, apply differen…