LPINNs: First-Layer Gated Localization for Physics-Informed Neural Networks
ScientificML
LPINNs propose multiplying the first hidden activation of a dense PINN by input-dependent localization functions, endowing first-layer units with receptive fields to improve optimization on long domains and for high-order operators without domain partitioning.
See LICENSE file Physics-Informed Neural NetworksPINN EnhancementNeural Network Localization