3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.PL2022
Symbolic Abstract Heaps for Polymorphic Information-flow Guard Inference (Extended Version)
Nicolas Berthier, Narges Khakpour
In the realm of sound object-oriented program analyses for information-flow control, very few approaches adopt flow-sensitive abstractions of the heap that enable a precise modelin…
cs.SE2021★ 2 cited
Tutorials on Testing Neural Networks
Nicolas Berthier, Youcheng Sun, Wei Huang +3
Deep learning achieves remarkable performance on pattern recognition, but can be vulnerable to defects of some important properties such as robustness and security. This tutorial i…
cs.LG2021★ 3 cited
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features
Nicolas Berthier, Amany Alshareef, James Sharp +2
Intensive research has been conducted on the verification and validation of deep neural networks (DNNs), aiming to understand if, and how, DNNs can be applied to safety critical ap…