3 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
Probabilistic Reach-Avoid for Bayesian Neural Networks
Matthew Wicker, Luca Laurenti, Andrea Patane +3
Model-based reinforcement learning seeks to simultaneously learn the dynamics of an unknown stochastic environment and synthesise an optimal policy for acting in it. Ensuring the s…
Individual Fairness in Bayesian Neural Networks
Alice Doherty, Matthew Wicker, Luca Laurenti +1
We study Individual Fairness (IF) for Bayesian neural networks (BNNs). Specifically, we consider the --individual fairness notion, which requires that, for any pair of input…
Gradient-Free Adversarial Attacks for Bayesian Neural Networks
Matthew Yuan, Matthew Wicker, Luca Laurenti
The existence of adversarial examples underscores the importance of understanding the robustness of machine learning models. Bayesian neural networks (BNNs), due to their calibrate…