English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We propose a methodology to explore and measure the pairwise correlationsthat exist between variables in a dataset. The methodology leverages copulasfor encoding dependence between two variables, state-of-the-art optimaltransport for providing a relevant geometry to the copulas, and clustering forsummarizing the main dependence patterns found between the variables. Some ofthe clusters centers can be used to parameterize a novel dependence coefficientwhich can target or forget specific dependence patterns. Finally, we illustrateand benchmark the methodology on several datasets. Code and numericalexperiments are available online for reproducible research.

Exploring and measuring non-linear correlations: Copulas, Lightspeed Transportation and Clustering