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20182025
most citedSurrogate Modeling for Fluid Flows Based on Physics-Constrained Deep Learning Without Simulation Data

1.1k citations · 2.5k across the 14 of their papers we have counts for

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Showing 2020Show all

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math.NA2020★ 313 cited

Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics

Weiqi Ji, Weilun Qiu, Zhiyu Shi +2

Recently developed physics-informed neural network (PINN) has achieved success in many science and engineering disciplines by encoding physics laws into the loss functions of the n…

math.DS2020★ 61 cited

Sparsity-promoting algorithms for the discovery of informative Koopman invariant subspaces

Shaowu Pan, Nicholas Arnold-Medabalimi, Karthik Duraisamy

Koopman decomposition is a non-linear generalization of eigen-decomposition, and is being increasingly utilized in the analysis of spatio-temporal dynamics. Well-known techniques s…