24 citations · 59 across the 12 of their papers we have counts for
3 papers · 1 filter
The Limitations of Model Uncertainty in Adversarial Settings
Kathrin Grosse, David Pfaff, Michael Thomas Smith +1
Machine learning models are vulnerable to adversarial examples: minor perturbations to input samples intended to deliberately cause misclassification. While an obvious security thr…
Gaussian Process Regression for Binned Data
Michael Thomas Smith, Mauricio A Alvarez, Neil D Lawrence
Many datasets are in the form of tables of binned data. Performing regression on these data usually involves either reading off bin heights, ignoring data from neighbouring bins or…
Killing four birds with one Gaussian process: the relation between different test-time attacks
Kathrin Grosse, Michael T. Smith, Michael Backes
In machine learning (ML) security, attacks like evasion, model stealing or membership inference are generally studied in individually. Previous work has also shown a relationship b…