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 introduce Clique Matrices as an alternative representation of undirectedgraphs, being a generalisation of the incidence matrix representation. Here weuse clique matrices to decompose a graph into a set of possibly overlappingclusters, de ned as well-connected subsets of vertices. The decomposition isbased on a statistical description which encourages clusters to be wellconnected and few in number. Inference is carried out using a variationalapproximation. Clique matrices also play a natural role in parameterisingpositive de nite matrices under zero constraints on elements of the matrix. Weshow that clique matrices can parameterise all positive de nite matricesrestricted according to a decomposable graph and form a structured FactorAnalysis approximation in the non-decomposable case.

Clique Matrices for Statistical Graph Decomposition and Parameterising Restricted Positive Definite Matrices