Unsupervised Adaptation of PDE Foundation Models
The episode reviews a paper that adapts PDE foundation models to new equations without ground-truth labels, using physics residuals and boundary conditions as supervision. The hosts discuss the method's architecture, results on benchmarks, and limitations, concluding that equations alone can nearly match supervised performance.