A discrete-time random feature method with IMEX-RK time stepping derives a global error estimate and achieves 10^{-6} relative L2 errors with third-order convergence on Allen-Cahn, Burgers, KdV, and Cahn-Hilliard equations.
Physics-informed neural networks (pinns) for fluid mechanics: A review
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A Discrete-Time Random Feature Method for Nonlinear Evolution Equations with Implicit-Explicit Runge--Kutta Time Stepping
A discrete-time random feature method with IMEX-RK time stepping derives a global error estimate and achieves 10^{-6} relative L2 errors with third-order convergence on Allen-Cahn, Burgers, KdV, and Cahn-Hilliard equations.