A domain-decomposition subspace neural network method solves linear and nonlinear PDEs with errors down to 1e-13 and lower training cost than PINN, DGM, DRM, and LocELM on 1D/2D benchmarks.
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Domain Decomposition Subspace Neural Network Method for Solving Linear and Nonlinear Partial Differential Equations
A domain-decomposition subspace neural network method solves linear and nonlinear PDEs with errors down to 1e-13 and lower training cost than PINN, DGM, DRM, and LocELM on 1D/2D benchmarks.