mlsanityData to 14 Oct 2026

Effective Estimation of the Dimensions of a Manifold from Random Samples

arXiv 2209.01839 ↗First posted 5 Sep 2022cs.CG math.GTcited by 1

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Abstract (arXiv)

We give explicit theoretical and heuristical bounds for how big does a data set sampled from a reach-1 submanifold M of euclidian space need to be, to be able to estimate the dimension of M with 90% confidence.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 5 Sep 2022.

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Citing papers per year: 2023: 1.

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  1. 2023CA-PCA: Manifold Dimension Estimation, Adapted for Curvaturecited by 4