Feb. 12, 2024, 5:43 a.m. | Nick Whiteley Annie Gray Patrick Rubin-Delanchy

cs.LG updates on arXiv.org arxiv.org

The Manifold Hypothesis is a widely accepted tenet of Machine Learning which asserts that nominally high-dimensional data are in fact concentrated near a low-dimensional manifold, embedded in high-dimensional space. This phenomenon is observed empirically in many real world situations, has led to development of a wide range of statistical methods in the last few decades, and has been suggested as a key factor in the success of modern AI technologies. We show that rich and sometimes intricate manifold structure in …

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