27 citations · 152 across the 28 of their papers we have counts for
4 papers · 1 filter
Assessing Robustness of Text Classification through Maximal Safe Radius Computation
Emanuele La Malfa, Min Wu, Luca Laurenti +3
Neural network NLP models are vulnerable to small modifications of the input that maintain the original meaning but result in a different prediction. In this paper, we focus on rob…
Probabilistic Safety for Bayesian Neural Networks
Matthew Wicker, Luca Laurenti, Andrea Patane +1
We study probabilistic safety for Bayesian Neural Networks (BNNs) under adversarial input perturbations. Given a compact set of input points, , we study t…
Safety Verification of Unknown Dynamical Systems via Gaussian Process Regression
John Jackson, Luca Laurenti, Eric Frew +1
The deployment of autonomous systems that operate in unstructured environments necessitates algorithms to verify their safety. This can be challenging due to, e.g., black-box compo…
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Ginevra Carbone, Matthew Wicker, 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…