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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Letting $\mathcal{M}$ denote the space of finite measures on $\mathbb{N}$,and $\mu_\lambda\in\mathcal{M}$ denote the Poisson distribution with parameter$\lambda$, the function $W:[0,1]^2\to\mathcal{M}$ given by \[ W(x,y)=\mu_{c\logx\log y} \] is called the PAG graphon with density $c$. It is known that thisis the limit, in the multigraph homomorphism sense, of the dense PreferentialAttachment Graph (PAG) model with edge density $c$. This graphon can then inturn be used to generate the so-called W-random graphs in a natural way. Theaim of this paper is to compare the dense PAG model with the W-random graphmodel obtained from the corresponding graphon. Motivated by the multigraphlimit theory, we investigate the expected jumble norm distance of the twomodels in terms on the number of vertices $n$. We present a coupling for whichthe expectation can be bounded from above by $O(\log^2 n\cdot n^{-1/3})$, andprovide a universal lower bound that is coupling independent, but with a worseexponent.

On the dense Preferential Attachment Graph models and their graphon induced counterpart