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

Neural networks are increasingly relied upon as components of complexsafety-critical systems such as autonomous vehicles. There is high demand fortools and methods that embed neural network verification in a largerverification cycle. However, neural network verification is difficult due to awide range of verification properties of interest, each typically only amenableto verification in specialised solvers. In this paper, we show how Imandra, afunctional programming language and a theorem prover originally designed forverification, validation and simulation of financial infrastructure can offer aholistic infrastructure for neural network verification. We develop a novellibrary CheckINN that formalises neural networks in Imandra, and coversdifferent important facets of neural network verification.

CheckINN: Wide Range Neural Network Verification in Imandra (Extended)