What Artificial Intelligence (AI) - Assessment of the Robustness of Neural Networks - Part 1: Overview requires
This technical report provides an overview of existing methods to assess the robustness of neural networks, focusing on formal verification and statistical testing approaches…
This is a preview. The full record adds the complete summary, 10 workflow steps, 11 schema fields and 8 primary citations. Start a free trial or see pricing.
Pillar: AI Governance & Law · Authority: International Organization for Standardization (ISO) · Version: 1.0.1 · Last updated:
Primary source: https://www.iso.org/standard/77609.html
SHA-256 integrity: f885db8f51ca911122bc50be14e40e9daf7de48c6195094b7e1a4dde74e280a7
Primary Citations — 8 traced to source
- ISO/IEC TR 24029-1:2021, Clause 5.3 - Threat modelling for neural networks
- ISO/IEC TR 24029-1:2021, Clause 6.2 - Overview of robustness assessment methods
+ 6 more citations (full bibliography, deterministic workflow, actionable schema and crosswalks) included in the vault unlock — $0.01 via Skyfire / L402 / Direct Base USDC.
Access
- Discovery (free): /api/v1/nodes/iso-iec-24029-1-robustness-neural-networks.json — 6-field metadata
- Vault (full node): /api/v1/vault/nodes/iso-iec-24029-1-robustness-neural-networks.json — full 13-key payload, $0.01 USDC (L402/Skyfire/Direct Base)
- Canonical URL: https://bidda.com/intelligence/iso-iec-24029-1-robustness-neural-networks
- Back to registry: Browse all 10,102 compliance nodes