266 citations · 619 across the 8 of their papers we have counts for
8 papers
Neural Additive Models: Interpretable Machine Learning with Neural Nets
Rishabh Agarwal, Levi Melnick, Nicholas Frosst +4
Deep neural networks (DNNs) are powerful black-box predictors that have achieved impressive performance on a wide variety of tasks. However, their accuracy comes at the cost of int…
Deflecting Adversarial Attacks
Yao Qin, Nicholas Frosst, Colin Raffel +2
There has been an ongoing cycle where stronger defenses against adversarial attacks are subsequently broken by a more advanced defense-aware attack. We present a new approach towar…
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
Yao Qin, Nicholas Frosst, Sara Sabour +3
Adversarial examples raise questions about whether neural network models are sensitive to the same visual features as humans. In this paper, we first detect adversarial examples or…
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
Nicholas Frosst, Nicolas Papernot, Geoffrey Hinton
We explore and expand the to measure the of class manifolds in representation space: i.e., how close pairs of points f…
SMILER: Saliency Model Implementation Library for Experimental Research
Calden Wloka, Toni Kunić, Iuliia Kotseruba +4
The Saliency Model Implementation Library for Experimental Research (SMILER) is a new software package which provides an open, standardized, and extensible framework for maintainin…
DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules
Nicholas Frosst, Sara Sabour, Geoffrey Hinton
We present a simple technique that allows capsule models to detect adversarial images. In addition to being trained to classify images, the capsule model is trained to reconstruct…
Distilling a Neural Network Into a Soft Decision Tree
Nicholas Frosst, Geoffrey Hinton
Deep neural networks have proved to be a very effective way to perform classification tasks. They excel when the input data is high dimensional, the relationship between the input…
Dynamic Routing Between Capsules
Sara Sabour, Nicholas Frosst, Geoffrey E Hinton
A capsule is a group of neurons whose activity vector represents the instantiation parameters of a specific type of entity such as an object or an object part. We use the length of…