Adversarial robustness guarantees for Gaussian processes
Gaussian processes (GPs) enable principled computation of model uncertainty, making them attractive for safety-critical applications. Such scenarios demand that GP decisions are not only accurate, but also robust to perturbations. In this paper we present a framework to analyse adversarial robustnes...
| Hoofdauteurs: | , , , , , |
|---|---|
| Formaat: | Journal article |
| Taal: | English |
| Gepubliceerd in: |
Journal of Machine Learning Research
2022
|