DropAttack
DropAttack
**DropAttack** is an adversarial training method that adds intentionally worst-case adversarial perturbations to both the input and hidden layers in different dimensions and minimizes the adversarial risks generated by each layer.
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks
https://paperswithcode.com/paper/dropattack-a-masked-weight-adversarial
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks