We study the problem of certifying the robustness of Bayesian neural net...
In this paper, we introduce BNN-DP, an efficient algorithmic framework f...
We study Individual Fairness (IF) for Bayesian neural networks (BNNs).
S...
Vulnerability to adversarial attacks is one of the principal hurdles to ...
We consider the problem of certifying the individual fairness (IF) of
fe...
We consider the problem of computing reach-avoid probabilities for itera...
Gaussian processes (GPs) enable principled computation of model uncertai...
We consider adversarial training of deep neural networks through the len...
We study probabilistic safety for Bayesian Neural Networks (BNNs) under
...
Vulnerability to adversarial attacks is one of the principal hurdles to ...
Gaussian Processes (GPs) are widely employed in control and learning bec...
We consider Bayesian classification with Gaussian processes (GPs) and de...
We introduce a probabilistic robustness measure for Bayesian Neural Netw...
Bayesian inference and Gaussian processes are widely used in application...