Neural frames: A Tool for Studying the Tangent Bundles Underlying Image Datasets and How Deep Learning Models Process Them. (arXiv:2211.10558v1 [cs.LG])

The assumption that many forms of high-dimensional data, such as images,
actually live on low-dimensional manifolds, sometimes known as the manifold
hypothesis, underlies much of our intuition for how and why deep learning
works. Despite the central role that they play in our intuition, data manifolds
are surprisingly hard to measure in the case of high-dimensional, sparsely
sampled image datasets. This is particularly frustrating since the capability
to measure data manifolds would provide a revealing window into the inner
workings …

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