1 citations · 1 across the 7 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2026
A probabilistic framework for online test-time adaptation
Daniel Corrales, David Ríos Insua
This paper presents a probabilistic framework for online test-time adaptation problems. In them, a model is trained on labeled data but must adapt to unlabeled data at test time un…
stat.ML2025
A unifying Bayesian framework for adversarial robustness
Pablo G. Arce, Roi Naveiro, David Ríos Insua
The vulnerability of machine learning models to adversarial attacks remains a critical societal security challenge. Traditional defenses, such as adversarial training, typically ro…
stat.ML2025
Evasion Attacks Against Bayesian Predictive Models
Pablo G. Arce, Roi Naveiro, David Ríos Insua
There is an increasing interest in analyzing the behavior of machine learning systems against adversarial attacks. However, most of the research in adversarial machine learning has…