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The embedding dimension of Laplacian eigenfunction maps

arXiv 1605.01643 ↗First posted 4 May 2016stat.ML cs.CV math.DGcited by 8

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Abstract (arXiv)

Any closed, connected Riemannian manifold M can be smoothly embedded by its Laplacian eigenfunction maps into ℝm for some m. We call the smallest such m the maximal embedding dimension of M. We show that the maximal embedding dimension of M is bounded from above by a constant depending only on the dimension of M, a lower bound for injectivity radius, a lower bound for Ricci curvature, and a volume bound. We interpret this result for the case of surfaces isometrically immersed in ℝ3, showing that the maximal embedding dimension only depends on bounds for the Gaussian curvature, mean curvature, and surface area. Furthermore, we consider the relevance of these results for shape registration.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2016.

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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 3; 2025: 1; 2026: 1.

8 papers.