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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The generation of accurate neutrino-nucleus cross-section models needed forneutrino oscillation experiments require simultaneously the description of manydegrees of freedom and precise calculations to model nuclear responses. Thedetailed calculation of complete models makes the Monte Carlo generators slowand impractical. We present Exhaustive Neural Importance Sampling (ENIS), amethod based on normalizing flows to find a suitable proposal density forrejection sampling automatically and efficiently, and discuss how thistechnique solves common issues of the rejection algorithm.

Exhaustive Neural Importance Sampling applied to Monte Carlo event generation