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...

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Bibliografische gegevens
Hoofdauteurs: Patane, A, Blaas, A, Laurenti, L, Cardelli, L, Roberts, S, Kwiatkowska, M
Formaat: Journal article
Taal:English
Gepubliceerd in: Journal of Machine Learning Research 2022