# Variable selection in functional regression models: a review

arXiv: https://arxiv.org/abs/2401.14867 · HTML: https://mlsanity.com/paper/2401.14867/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jan 2024.

## Built on by (most cited first, 2 of 2)

- [Local regression on path spaces with signature metrics](https://mlsanity.com/paper/2510.16728/) (2025)
- [Deep Gaussian Processes for Functional Maps](https://mlsanity.com/paper/2510.22068/) (2025)

## Abstract (arXiv)

Despite of various similar features, Functional Data Analysis and High-Dimensional Data Analysis are two major fields in Statistics that grew up recently almost independently one from each other. The aim of this paper is to propose a survey on methodological advances for variable selection in functional regression, which is typically a question for which both functional and multivariate ideas are crossing. More than a simple survey, this paper aims to promote even more new links between both areas.