Fisher information and the geometry of memorization in neural networks.

arXiv:2610.16161v1 Announce Type: cross Abstract: A fruitful approach towards understanding generalization in machine learning involves characterizing how models separate generalizable structure from idiosyncratic or even corrupted features of training data. F