Search Results for author:
Found 2 papers, 1 papers with code
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness
We demonstrate that training the networks to have interpretable gradients improves their robustness to adversarial perturbations.
NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks
The problem of explaining deep learning models, and model predictions generally, has attracted intensive interest recently.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
