# Kernel smoothing on manifolds

arXiv: https://arxiv.org/abs/2601.16777 · HTML: https://mlsanity.com/paper/2601.16777/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jan 2026.

## Built on by (most cited first, 1 of 1)

- [Kernel-Gradient Drifting Models](https://mlsanity.com/paper/2605.10727/) (2026)

## Abstract (arXiv)

Under the assumption that data lie on a compact (unknown) manifold without boundary, we derive finite sample bounds for kernel smoothing and its (first and second) derivatives, and we establish asymptotic normality through Berry-Esseen type bounds. Special cases include kernel density estimation, kernel regression and the heat kernel signature. Connections to the graph Laplacian are also discussed.