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cs.LG2022★ 1 cited
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
Luca Bortolussi, Ginevra Carbone, Luca Laurenti +3
Vulnerability to adversarial attacks is one of the principal hurdles to the adoption of deep learning in safety-critical applications. Despite significant efforts, both practical a…
cs.LG2022
Individual Fairness Guarantees for Neural Networks
Elias Benussi, Andrea Patane, Matthew Wicker +2
We consider the problem of certifying the individual fairness (IF) of feed-forward neural networks (NNs). In particular, we work with the --IF formulation, which, given a NN…