Cover Image

Kernel smoothing on manifolds

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bae, Eunseong, Polonik, Wolfgang
Format:	Preprint
Published:	2026
Subjects:	Statistics Theory Machine Learning Differential Geometry
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Asymptotic expansions for spectral convergence of compact self-adjoint operators on general spectral subsets, with application to kernel Gram matrices
by: Bae, Eunseong, et al.
Published: (2026)

Categorical and geometric methods in statistical, manifold, and machine learning
by: Lê, Hông Vân, et al.
Published: (2025)

Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality Reduction
by: Herrera-Esposito, Daniel, et al.
Published: (2025)

On Higher-Order Geometric Refinements of Classical Covariance Asymptotics: An Approach via Intrinsic and Extrinsic Information Geometry
by: Amir, Malik, et al.
Published: (2026)

Geometric Gaussian Approximations of Probability Distributions
by: Da Costa, Nathaël, et al.
Published: (2025)

Riemannian Archetypal Analysis: Interpretable non-linear data analysis on deformed star distributions
by: Diepeveen, Willem, et al.
Published: (2026)

Conformal Transformation of Kernels: A Geometric Perspective on Text Classification
by: Rădulescu, Ioana, et al.
Published: (2024)

Hessian Geometry of Latent Space in Generative Models
by: Lobashev, Alexander, et al.
Published: (2025)

Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps
by: Shi, Zhaoyang, et al.
Published: (2024)

Convergence of Hessian estimator from random samples on a manifold with boundary
by: Chen, Chih-Wei, et al.
Published: (2023)

Algorithms for ridge estimation with convergence guarantees
by: Qiao, Wanli, et al.
Published: (2021)

Covariance as a commutator
by: Meixide, Carlos García
Published: (2025)

On Logit Weibull Manifold
by: Assandje, Prosper Rosaire Mama, et al.
Published: (2025)

Exploring Stochastic Mean Curvature Flow on Networks Using Ito Calculus
by: Bahadursingh, Roman
Published: (2024)

Robust boundary detection and density estimation using doubly stochastic scaling of the Gaussian kernel
by: Kohli, Dhruv, et al.
Published: (2024)

Stability and Statistical Inversion of Travel time Tomography
by: Tarikere, Ashwin, et al.
Published: (2023)

Riemannian radial distributions on Riemannian symmetric spaces: Optimal rates of convergence for parameter estimation
by: Chen, Hengchao
Published: (2024)

The Long Time Limit of Diffusion Means
by: Düsberg, Till, et al.
Published: (2024)

Kernel-Gradient Drifting Models
by: Esteban-Casadevall, Maria, et al.
Published: (2026)

Multivariate Gaussian Approximation for Random Forest via Region-based Stabilization
by: Shi, Zhaoyang, et al.
Published: (2024)

Geometric Learning with Positively Decomposable Kernels
by: Da Costa, Nathael, et al.
Published: (2023)

Manifolds with kinks and the asymptotic behavior of the graph Laplacian operator with Gaussian kernel
by: Pal, Susovan, et al.
Published: (2025)

On Closed-Form Expressions for the Fisher-Rao Distance
by: Miyamoto, Henrique K., et al.
Published: (2023)

Refining Cramér-Rao Bound With Multivariate Parameters: An Extrinsic Geometry Perspective
by: Krishnan, Sunder Ram
Published: (2025)

Geometric Interpretation of Brownian Motion on Riemannian Manifolds
by: Lee, Taeyoung, et al.
Published: (2025)

On statistics which are almost sufficient from the viewpoint of the Fisher metrics
by: Yamaguchi, Kaori, et al.
Published: (2023)

Improving Cramér-Rao Bound And Its Variants: An Extrinsic Geometry Perspective
by: Krishnan, Sunder Ram
Published: (2025)

Cartan moving frames and the data manifolds
by: Tron, Eliot, et al.
Published: (2024)

Neural and numerical methods for $\mathrm{G}_2$-structures on contact Calabi-Yau 7-manifolds
by: Heyes, Elli, et al.
Published: (2026)

Tessellation Groups, Harmonic Analysis on Non-compact Symmetric Spaces and the Heat Kernel in view of Cartan Convolutional Neural Networks
by: Fré, Pietro, et al.
Published: (2025)

Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
by: Shi, Zhaoyang, et al.
Published: (2024)

Persistent de Rham-Hodge Laplacians in Eulerian representation for manifold topological learning
by: Su, Zhe, et al.
Published: (2024)

The Fisher metric as a metric on the cotangent bundle
by: Nagaoka, Hiroshi
Published: (2023)

Canonical normalizing flows for manifold learning
by: Flouris, Kyriakos, et al.
Published: (2023)

Adversarial attacks on neural networks through canonical Riemannian foliations
by: Tron, Eliot, et al.
Published: (2022)

Quantum Geometry insights in Deep Learning
by: Combe, Noémie C.
Published: (2025)

On Statistical Inference for Rates of Change in Spatial Processes over Riemannian Manifolds
by: Li, Didong, et al.
Published: (2026)

Two-Sample Tests for Optimal Lifts, Manifold Stability and Reverse Labeling Reflection Shap
by: Van, Do Tran, et al.
Published: (2025)

Cartan meets Cramér-Rao
by: Krishnan, Sunder Ram
Published: (2025)

Transversality Methods for Homotopy Groups of Stable Loci in Affine GIT Quotients
by: Wang, Yizhi
Published: (2025)