Neuro-Symbolic Verification of Deep Neural Networks

Understand

Formal verification has emerged as a powerful approach to ensure the safety and reliability of deep neural networks.

• However, current verification tools are limited to only a handful of properties that can be expressed as first-order constraints over the inputs and output of a network.
• While adversarial robustness and fairness fall under this category, many real-world properties (e.g., "an autonomous vehicle has to stop in front of a stop sign") remain outside the scope of existing verification technology.
• To mitigate this severe practical restriction, we introduce a novel framework for verifying neural networks, named neuro-symbolic verification.