4 papers · 1 filter
Risk-Averse Certification of Bayesian Neural Networks
Xiyue Zhang, Zifan Wang, Yulong Gao +3
In light of the inherently complex and dynamic nature of real-world environments, incorporating risk measures is crucial for the robustness evaluation of deep learning models. In t…
FAST: Boosting Uncertainty-based Test Prioritization Methods for Neural Networks via Feature Selection
Jialuo Chen, Jingyi Wang, Xiyue Zhang +4
Due to the vast testing space, the increasing demand for effective and efficient testing of deep neural networks (DNNs) has led to the development of various DNN test case prioriti…
PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks
Xiyue Zhang, Benjie Wang, Marta Kwiatkowska +1
Most methods for neural network verification focus on bounding the image, i.e., set of outputs for a given input set. This can be used to, for example, check the robustness of neur…
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks
Matthias König, Xiyue Zhang, Holger H. Hoos +2
The ubiquity of deep learning algorithms in various applications has amplified the need for assuring their robustness against small input perturbations such as those occurring in a…