A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability XiaoweiHuang, ...XinpingYi, inComputer Science Review, 2020 8.4Verification completeness Additional to the properties we mentioned in Section3, the correctness of ...
Therefore, the interpretability of the developed models can provide transparent insights into the decision-making process. The next question is, 'What are the solution tools and techniques to achieve the aim of this study?'. Creating an evaluation and benchmarking framework for the selection of ...
Integrating ad hoc sorting in training, the SCQRNN ensures non-intersecting quantiles, boosting model reliability and interpretability. We demonstrate that the SCQRNN not only prevents quantile crossing and reduces computational complexity but also achieves faster convergence than traditional models. This ...