Course Description
Introduces physics-aware deep learning (PADL), an emerging approach that embeds physical laws into neural networks for accurate, efficient modeling. Topics include differential equations, physics-informed neural networks, neural operators, and PyTorch implementation. Students gain both theoretical foundations and practical skills to apply PADL across disciplines.
