2026
Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment
ICML 2026poster
Physics-informed diffusion models typically impose PDE constraints only on the final output, leaving intermediate features unconstrained. This can enable shortcut solutions that fit training statistics yet generalize poorly under shifted boundary conditions. We introduce \textbf{REPA-P}, a \emph{tea…