AI RESEARCH
Training Deep Visual Networks Beyond Loss and Accuracy Through a Dynamical Systems Approach
arXiv CS.AI
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ArXi:2604.09716v1 Announce Type: cross 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 internal representations change during