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Abstract
We demonstrate that the Conditional Entropy Bottleneck (CEB) can improve
model robustness. CEB is an easy strategy to implement and works in tandem with
data augmentation procedures. We report results of a large scale adversarial
robustness study on CIFAR-10, as well as the ImageNet-C Common Corruptions
Benchmark, ImageNet-A, and PGD attacks.