AI RESEARCH
An adaptive wavelet-based PINN for problems with localized high-magnitude source
arXiv CS.LG
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ArXi:2604.28180v1 Announce Type: new In recent years, physics-informed neural networks (PINNs) have gained significant attention for solving differential equations, although they suffer from two fundamental limitations, namely, spectral bias inherent in neural networks and loss imbalance arising from multiscale phenomena. This paper proposes an adaptive wavelet-based PINN (AW-PINN) to address the extreme loss imbalance characteristic of problems with localized high-magnitude source terms.