AI RESEARCH
PILIR: Physics-Informed Local Implicit Representation
arXiv CS.LG
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ArXi:2605.00385v1 Announce Type: new Physics-Informed Neural Networks have become a powerful mesh-free method for solving partial differential equations, but their performance is often limited by spectral bias. Specifically, in standard MLPs used in PINNs, the global parameter coupling causes the model to prioritize learning low-frequency components, resulting in slow convergence for high-frequency details. To overcome this limitation, we