Training Deep Visual Networks Beyond Loss and Accuracy Through a Dynamical Systems Approach
arXiv:2604.09716v1 Announce Type: cross
Abstract: Deep visual recognition models are usually trained and evaluated using metrics such as loss and accuracy. While these measures show whether a model is improving, they reveal very little about how its i…