# Signature features with the visibility transformation

arXiv: https://arxiv.org/abs/2004.04006 · HTML: https://mlsanity.com/paper/2004.04006/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2020.

## Built on by (most cited first, 3 of 3)

- [Modelling Paralinguistic Properties in Conversational Speech to Detect Bipolar Disorder and Borderline Personality Disorder](https://mlsanity.com/paper/2102.09607/) (2021)
- [Generating Financial Time Series by Matching Random Convolutional Features](https://mlsanity.com/paper/2606.05138/) (2026)
- [Signature Approach for Contextual Bandits with Nonlinear and Path-dependent Rewards](https://mlsanity.com/paper/2605.10313/) (2026)

## Abstract (arXiv)

In this paper we put the visibility transformation on a clear theoretical footing and show that this transform is able to embed the effect of the absolute position of the data stream into signature features in a unified and efficient way. The generated feature set is particularly useful in pattern recognition tasks, for its simplifying role in allowing the signature feature set to accommodate nonlinear functions of absolute and relative values.