Mollifier Layers replace recursive autodiff with analytic mollifier convolutions, yielding efficient and noise-robust high-order derivatives for inverse PDE learning.
The Hadamard- PINN for PDE inverse problems: Convergence with distant initial guesses
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Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning
Mollifier Layers replace recursive autodiff with analytic mollifier convolutions, yielding efficient and noise-robust high-order derivatives for inverse PDE learning.