A secant-based adaptive correction augments first-order optimizers to improve convergence speed, stability, and accuracy when training PINNs on challenging PDEs.
Physics-guided, physics-informed, and physics-encoded neural networks and operators in scientific computing: Fluid and solid mechanics.J
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Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks
A secant-based adaptive correction augments first-order optimizers to improve convergence speed, stability, and accuracy when training PINNs on challenging PDEs.