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 present a novel sampling framework for probabilistic programs. Theframework combines two recent ideas -- \emph{control-data separation} and\emph{logical condition propagation} -- in a nontrivial manner so that the twoideas boost the benefits of each other. We implemented our algorithm on top ofAnglican. The experimental results demonstrate our algorithm's efficiency,especially for programs with while loops and rare observations.

Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs