1.5k citations · 5.7k across the 60 of their papers we have counts for
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Label-Consistent Backdoor Attacks
Alexander Turner, Dimitris Tsipras, Aleksander Madry
Deep neural networks have been demonstrated to be vulnerable to backdoor attacks. Specifically, by injecting a small number of maliciously constructed inputs into the training set,…
Image Synthesis with a Single (Robust) Classifier
Shibani Santurkar, Dimitris Tsipras, Brandon Tran +3
We show that the basic classification framework alone can be used to tackle some of the most challenging tasks in image synthesis. In contrast to other state-of-the-art approaches,…
Adversarial Robustness as a Prior for Learned Representations
Logan Engstrom, Andrew Ilyas, Shibani Santurkar +3
An important goal in deep learning is to learn versatile, high-level feature representations of input data. However, standard networks' representations seem to possess shortcomings…
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras +3
Adversarial examples have attracted significant attention in machine learning, but the reasons for their existence and pervasiveness remain unclear. We demonstrate that adversarial…
On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot +6
Correctly evaluating defenses against adversarial examples has proven to be extremely difficult. Despite the significant amount of recent work attempting to design defenses that wi…