Edge Accuracy Is Not Enough: Why Dynamics-Learned Structure Fails to Transfer to Inverse Problems
The study tested if structure learned from predicting system dynamics could be reliably transferred to source-localization tasks. While the learned structure met an edge-accuracy condition, it failed to transfer because approximation error dominates when the forward and inverse tasks require different optimal structures. This means physics-based structure transfer only works when the learned graph significantly overlaps with the task's required spatial constraints.