A PINN framework with differentiable history switch, trial-solution enforcement, and segmented collocation is introduced for solving general first-order nonlinear delay differential equations.
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Physics Informed Neural Networks for Nonlinear Delay Differential Equations
A PINN framework with differentiable history switch, trial-solution enforcement, and segmented collocation is introduced for solving general first-order nonlinear delay differential equations.