Robust Explainability: A tutorial on gradient-based attribution methods for deep neural networks
Robust Explainability: A tutorial on gradient-based attribution methods for deep neural networks
With the rise of deep neural networks, the challenge of explaining the predictions of these networks has become increasingly recognized. While many methods for explaining the decisions of deep neural networks exist, there is currently no consensus on how to evaluate them. On the other hand, robustness is a popular …