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/

Zendy Plus

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

Zendy Tools

Zendy Open

We introduce hydra (hyperbolic distance recovery and approximation), a newmethod for embedding network- or distance-based data into hyperbolic space. Weshow mathematically that hydra satisfies a certain optimality guarantee: Itminimizes the `hyperbolic strain' between original and embedded data points.Moreover, it recovers points exactly, when they are located on a hyperbolicsubmanifold of the feature space. Testing on real network data we show that theembedding quality of hydra is competitive with existing hyperbolic embeddingmethods, but achieved at substantially shorter computation time. An extendedmethod, termed hydra+, outperforms existing methods in both computation timeand embedding quality.

Hydra: A method for strain-minimizing hyperbolic embedding of network- and distance-based data