Last summer I had the pleasure of working with a talented undergraduate researcher named Romain Speciel on a project that looked at how to regularize model ensembles in a way that improves robustness to adversarial examples. Our main concern was reducing the transferability of adversarial examples between models as that…

A recent attempt to improve the robustness of convolutional neural networks (CNNs) on image classification tasks has revealed an interesting link between robustness and interpretability. Models trained using adversarial training, a training procedure that augments training data with adversarial examples, have input gradients that qualitatively appear to be using more…