8 citations · 14 across the 5 of their papers we have counts for
15 papers
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…
Formal Control Synthesis for Stochastic Neural Network Dynamic Models
Steven Adams, Morteza Lahijanian, Luca Laurenti
Neural networks (NNs) are emerging as powerful tools to represent the dynamics of control systems with complicated physics or black-box components. Due to complexity of NNs, howeve…
Certification of Iterative Predictions in Bayesian Neural Networks
Matthew Wicker, Luca Laurenti, Andrea Patane +3
We consider the problem of computing reach-avoid probabilities for iterative predictions made with Bayesian neural network (BNN) models. Specifically, we leverage bound propagation…
Adversarial Robustness Guarantees for Gaussian Processes
Andrea Patane, Arno Blaas, Luca Laurenti +3
Gaussian processes (GPs) enable principled computation of model uncertainty, making them attractive for safety-critical applications. Such scenarios demand that GP decisions are no…
Bayesian Inference with Certifiable Adversarial Robustness
Matthew Wicker, Luca Laurenti, Andrea Patane +3
We consider adversarial training of deep neural networks through the lens of Bayesian learning, and present a principled framework for adversarial training of Bayesian Neural Netwo…
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…