Antonio Vergari

Faithful concept bottleneck explanations are impossible without including all concepts, but probabilistic modeling and group lasso enable compact, faithful explanations.

Uncertainty-quantified neural surrogates can drastically enhance Bayesian inference efficiency for complex inverse problems, outperforming traditional methods in high-dimensional settings.

Predicting unseen links in knowledge graphs can often hinge on just a single half-link, revealing critical insights into model generalization.