2025
$\mathcal{I}$-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers
AISTATS 2025poster
As probabilistic models continue to permeate various facets of our society and contribute to scientific advancements, it becomes a necessity to go beyond traditional metrics such as predictive accuracy and error rates and assess their trustworthiness. Grounded in the competence-based theory of trust…