1 code implementation • 21 Jan 2024 • Ben Batten, Mehran Hosseini, Alessio Lomuscio
We introduce two algorithms for computing tight guarantees on the probabilistic robustness of Bayesian Neural Networks (BNNs).
1 code implementation • 23 May 2023 • Alessandro De Palma, Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio
In order to train networks for verified adversarial robustness, it is common to over-approximate the worst-case loss over perturbation regions, resulting in networks that attain verifiability at the expense of standard performance.
no code implementations • CVPR 2023 • Harleen Hanspal, Alessio Lomuscio
The deployment of perception systems based on neural networks in safety critical applications requires assurance on their robustness.
no code implementations • 28 Nov 2018 • Panagiotis Kouvaros, Alessio Lomuscio
We address the problem of verifying neural-based perception systems implemented by convolutional neural networks.
no code implementations • 22 Jun 2017 • Alessio Lomuscio, Lalit Maganti
We study the reachability problem for systems implemented as feed-forward neural networks whose activation function is implemented via ReLU functions.
no code implementations • 23 Jan 2014 • Francesco Belardinelli, Alessio Lomuscio
We investigate a class of first-order temporal-epistemic logics for reasoning about multi-agent systems.