2026
Optimization Dynamics of Equivariant and Augmented Neural Networks
ICML 2026poster
We investigate the optimization of neural networks on symmetric data, and compare the strategy of constraining the architecture to be equivariant to that of using data augmentation. Our analysis reveals that the relative geometry of the admissible and the equivariant layers, respectively, plays a ke…