Little is known about how deep networks interact with structure in data. An important aspect of this structure is symmetry (e.g., pose transformations). Here, we (w/ @stphtphsn.bsky.social) study the generalization ability of deep networks on symmetric datasets: arxiv.org/abs/2412.11521 (1/n)
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
Symmetries (transformations by group actions) are present in many datasets, and leveraging them holds significant promise for improving predictions in machine learning. In this work, we aim to underst...
arxiv.org