# Nonparametric Universal Copula Modeling

arXiv: https://arxiv.org/abs/1912.05503 · HTML: https://mlsanity.com/paper/1912.05503/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Dec 2019.

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

- [Abductive Inference and C. S. Peirce: 150 Years Later](https://mlsanity.com/paper/2111.08054/) (2021)
- [2-Cats: 2D Copula Approximating Transforms](https://mlsanity.com/paper/2309.16391/) (2023)

## Abstract (arXiv)

To handle the ubiquitous problem of "dependence learning," copulas are quickly becoming a pervasive tool across a wide range of data-driven disciplines encompassing neuroscience, finance, econometrics, genomics, social science, machine learning, healthcare and many more. Copula (or connection) functions were invented in 1959 by Abe Sklar in response to a query of Maurice Frechet. After 60 years, where do we stand now? This article provides a history of the key developments and offers a unified perspective.