The Limitations of Model Uncertainty in Adversarial Settings

no code implementations • 6 Dec 2018 • Kathrin Grosse, David Pfaff, Michael Thomas Smith, Michael Backes

Machine learning models are vulnerable to adversarial examples: minor perturbations to input samples intended to deliberately cause misclassification.

BIG-bench Machine Learning Gaussian Processes

How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models

no code implementations • 17 Nov 2017 • Kathrin Grosse, David Pfaff, Michael Thomas Smith, Michael Backes

In this paper, we leverage Gaussian Processes to investigate adversarial examples in the framework of Bayesian inference.

Bayesian Inference Gaussian Processes