A case study shows that differentiable-logic training improves local robustness of a small path-centring network, but current verifiers fail on the regression architecture and the title's 'formally verified' claim is not achieved.
In: Proceedings of the 35th International Conference on Machine Learning, PMLR, pp
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Creating a Formally Verified Neural Network for Autonomous Navigation: An Experience Report
A case study shows that differentiable-logic training improves local robustness of a small path-centring network, but current verifiers fail on the regression architecture and the title's 'formally verified' claim is not achieved.