A unified PINN framework uses residual-loss anomaly analysis to jointly locate regime transitions and estimate piecewise parameters in nonlinear dynamical systems.
Lux, Estimation of regime-switching diffusions via fourier transforms, Statistics and Computing 34 (2) (2024) 88
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Residual-loss Anomaly Analysis of Physics-Informed Neural Networks: An Inverse Method for Change-point Detection in Nonlinear Dynamical Systems with Regime Switching
A unified PINN framework uses residual-loss anomaly analysis to jointly locate regime transitions and estimate piecewise parameters in nonlinear dynamical systems.