When lookout sees crackle: Anomaly detection via kernel density estimation
Methodology
2026-03-25 v1
Abstract
We present an updated version of lookout -- an algorithm for detecting anomalies using kernel density estimates with bandwidth based on Rips death diameters -- with theoretical guarantees. The kernel density estimator for updated lookout is shown to be consistent, and the proposed multivariate scaling is robust and efficient. We show our updated algorithm performs better than the previous version on diverse examples.
Keywords
Cite
@article{arxiv.2603.22636,
title = {When lookout sees crackle: Anomaly detection via kernel density estimation},
author = {Rob J Hyndman and Sevvandi Kandanaarachchi and Katharine Turner},
journal= {arXiv preprint arXiv:2603.22636},
year = {2026}
}
Comments
30 pages