138 citations · 597 across the 30 of their papers we have counts for
9 papers · 1 filter
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability
Xiaowei Huang, Daniel Kroening, Wenjie Ruan +5
In the past few years, significant progress has been made on deep neural networks (DNNs) in achieving human-level performance on several long-standing tasks. With the broader deplo…
Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control
Rhiannon Michelmore, Marta Kwiatkowska, Yarin Gal
A rise in popularity of Deep Neural Networks (DNNs), attributed to more powerful GPUs and widely available datasets, has seen them being increasingly used within safety-critical do…
Equilibria-based Probabilistic Model Checking for Concurrent Stochastic Games
Marta Kwiatkowska, Gethin Norman, David Parker +1
Probabilistic model checking for stochastic games enables formal verification of systems that comprise competing or collaborating entities operating in a stochastic environment. De…
Robustness Guarantees for Bayesian Inference with Gaussian Processes
Luca Cardelli, Marta Kwiatkowska, Luca Laurenti +1
Bayesian inference and Gaussian processes are widely used in applications ranging from robotics and control to biological systems. Many of these applications are safety-critical an…
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees
Min Wu, Matthew Wicker, Wenjie Ruan +2
Despite the improved accuracy of deep neural networks, the discovery of adversarial examples has raised serious safety concerns. In this paper, we study two variants of pointwise r…
Reachability Analysis of Deep Neural Networks with Provable Guarantees
Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska
Verifying correctness of deep neural networks (DNNs) is challenging. We study a generic reachability problem for feed-forward DNNs which, for a given set of inputs to the network a…
Concolic Testing for Deep Neural Networks
Youcheng Sun, Min Wu, Wenjie Ruan +3
Concolic testing combines program execution and symbolic analysis to explore the execution paths of a software program. This paper presents the first concolic testing approach for…
Central Limit Model Checking
Luca Bortolussi, Luca Cardelli, Marta Kwiatkowska +1
We consider probabilistic model checking for continuous-time Markov chains (CTMCs) induced from Stochastic Reaction Networks (SRNs) against a fragment of Continuous Stochastic Logi…
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Norm
Wenjie Ruan, Min Wu, Youcheng Sun +3
Deployment of deep neural networks (DNNs) in safety- or security-critical systems requires provable guarantees on their correct behaviour. A common requirement is robustness to adv…