Search Results for author:
Found 6 papers, 2 papers with code
Tight Verification of Probabilistic Robustness in Bayesian Neural Networks
We introduce two algorithms for computing tight guarantees on the probabilistic robustness of Bayesian Neural Networks (BNNs).
Expressive Losses for Verified Robustness via Convex Combinations
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.
Efficient Verification of Neural Networks Against LVM-Based Specifications
The deployment of perception systems based on neural networks in safety critical applications requires assurance on their robustness.
Formal Verification of CNN-based Perception Systems
We address the problem of verifying neural-based perception systems implemented by convolutional neural networks.
An approach to reachability analysis for feed-forward ReLU neural networks
We study the reachability problem for systems implemented as feed-forward neural networks whose activation function is implemented via ReLU functions.
Interactions between Knowledge and Time in a First-Order Logic for Multi-Agent Systems: Completeness Results
We investigate a class of first-order temporal-epistemic logics for reasoning about multi-agent systems.
