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

Existing applications include a huge amount of knowledge that is out of reachfor deep neural networks. This paper presents a novel approach for integratingcalls to existing applications into deep learning architectures. Using thisapproach, we estimate each application's functionality with an estimator, whichis implemented as a deep neural network (DNN). The estimator is then embeddedinto a base network that we direct into complying with the application'sinterface during an end-to-end optimization process. At inference time, wereplace each estimator with its existing application counterpart and let thebase network solve the task by interacting with the existing application. Usingthis 'Estimate and Replace' method, we were able to train a DNN end-to-end withless data and outperformed a matching DNN that did not interact with theexternal application.

Estimate and Replace: A Novel Approach to Integrating Deep Neural Networks with Existing Applications