Physics-informed convolutional neural networks (PICNNs) have emerged as a powerful extension of physics-informed neural networks (PINNs), offering superior generalization and efficiency for solving ...

Paleoclimatic measurements serve to understand Earth System processes and evaluate climate model performances. However, their spatial coverage is generally sparse and unevenly distributed across the ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...