In this talk, I will introduce our novel Physics-Guided Diffusion Model (PGDM) for solving complex PDEs via downscaling, transforming low-resolution data into high-fidelity solutions. Our numerical experiments demonstrate that PGDM not only achieves computation speeds over ten times faster than traditional methods but also exceeds the accuracy of other data-driven approaches like FNO, particularly in limiting data scenarios.
