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Early Learning Shapes Later Directions Of Representation Change In Continual Learning
Representations continually change as a network learns new tasks. We ask whether early representational changes naturally form a geometric structure that continues to shape later learning. We identify a low-dimensional subspace of early representation drift, which we call a scaffold, and test whethe
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