Density estimators of Gaussian type on closed Riemannian manifolds
DOI10.1007/s10851-013-0460-5zbMath1310.62047OpenAlexW1985868117WikidataQ115383732 ScholiaQ115383732MaRDI QIDQ2513410
Washington Mio, Jonathan Bates
Publication date: 28 January 2015
Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10851-013-0460-5
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Information theory (general) (94A15) Heat and other parabolic equation methods for PDEs on manifolds (58J35) Vector distributions (subbundles of the tangent bundles) (58A30)
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Uses Software
Cites Work
- Kernel density estimation with spherical data
- Kernel density estimation via diffusion
- Nonparametric estimation of a probability density on a Riemannian manifold using Fourier expansions
- Towards a theoretical foundation for Laplacian-based manifold methods
- Spherical deconvolution
- A quadrature formula for the sphere of the 131st algebraic order of accuracy
- Scale space view of curve estimation.
- Application of fast spherical Fourier transform to density estimation
- An empirical Bayes approach to directional data and efficient computation on the sphere
- Kernel density estimation on Riemannian manifolds
- The Ubiquitous Heat Kernel
- Asymptotic Statistics
- Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
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