DeepRTE: Pre-trained Attention-based Neural Network for Radiative Tranfer

Researchers introduced DeepRTE, a neural network method utilizing pre-trained attention mechanisms to accurately and efficiently solve the steady-state Radiative Transfer Equation, which models radiation propagation in various scientific fields. Numerical experiments demonstrate the approach's high accuracy and computational benefits across applications like atmospheric transfer, heat transfer, and optical imaging.