# Root Laplacian Eigenmaps with their application in spectral embedding

arXiv: https://arxiv.org/abs/2302.02731 · HTML: https://mlsanity.com/paper/2302.02731/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 24 references that are in the map.
- First posted on arXiv 6 Feb 2023.

## Builds on (most cited first, 1 of 1)

- [Graph Signal Processing: Overview, Challenges and Applications](https://mlsanity.com/paper/1712.00468/) (2017)

## Abstract (arXiv)

The root laplacian operator or the square root of Laplacian which can be obtained in complete Riemannian manifolds in the Gromov sense has an analog in graph theory as a square root of graph-Laplacian. Some potential applications have been shown in geometric deep learning (spectral clustering) and graph signal processing.