Empirical Evidence for Simply Connected Decision Regions in Image Classifiers
The study tested whether closed loops inside deep neural network decision regions are simply connected, meaning they can be filled by surfaces without leaving the region. Researchers used an iterative quad-mesh filling procedure across six models and 6000 loops. The results show that label-preserving surfaces were successfully constructed for all tested loops, strongly suggesting these decision regions have a topological property beyond simple path connectivity.