Mary M. Maleckar

Latent PDE mapping for efficient physics-informed learning across geometries with limited data

Ingvild Askim Adde, Mary M. Maleckar, Gabriel Balaban

In this study, we introduce latent PDE mapping, a broadly applicable physics-informed learning technique designed to enable efficient geometric generalization with sparse training data. Latent PDE mapping pulls back geometry-specific PDE residuals and boundary conditions to a pre…Read more