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

For many applications, such as computing the expected value of differentmagnitudes, sampling from a known probability density function, the targetdensity, is crucial but challenging through the inverse transform. In thesecases, rejection and importance sampling require suitable proposal densities,which can be evaluated and sampled from efficiently. We will present a methodbased on normalizing flows, proposing a solution for the common problem ofexploding reverse Kullback-Leibler divergence due to the target density havingvalues of 0 in regions of the flow transformation. The performance of themethod will be demonstrated using a multi-mode complex density function.

Efficient sampling generation from explicit densities via Normalizing Flows