Jul 20, 2020
Transfer Learning with Adversarially Robust Models
We find that adversarially robust neural networks are better for downstream transfer learning than standard networks, despite having lower accuracy.
Jun 18, 2020
Noise or Signal: The Role of Backgrounds in Image Classification
To what extent to state-of-the-art vision models depend on image backgrounds?
May 25, 2020
From ImageNet to Image Classification
We take a closer look at the ImageNet dataset and identify ways in which it deviates from the underlying object recognition task.
May 19, 2020
Identifying Statistical Bias in Dataset Replication
Statistical bias in dataset reproduction studies can lead to skewed outcomes and observations.
Jun 6, 2019
Robustness Beyond Security: Computer Vision Applications
An off-the-shelf robust classifier can be used to perform a range of computer vision tasks beyond classification.
Jun 3, 2019
Robustness Beyond Security: Representation Learning
Representations induced by robust models align better with human perception, and allow for a number of downstream applications.
May 6, 2019
Adversarial Examples Are Not Bugs, They Are Features
A new perspective on adversarial perturbations
Apr 30, 2019
A Closer Look at Deep Policy Gradients (Part 3: Landscapes and Trust Regions)
In the second part of our analysis, we examine gradient estimate quality and the value function as a variance reducing baseline.
