21 citations · 39 across the 6 of their papers we have counts for
6 papers
Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches
Lukasz Mazur, Nenad Petrovic, James Pontes Miranda +3
Large language models (LLMs) offer new opportunities for interacting with complex software artifacts, such as software models, through natural language. They present especially pro…
Multi-Agent Optimization for Safety Analysis of Cyber-Physical Systems: Position Paper
Önder Gürcan, Nataliya Yakymets, Sara Tucci-Piergiovanni +1
Failure Mode, Effects and Criticality Analysis (FMECA) is one of the safety analysis methods recommended by most of the international standards. The classical FMECA is made in a fo…
Towards Dependable Autonomous Systems Based on Bayesian Deep Learning Components
Fabio Arnez, Huascar Espinoza, Ansgar Radermacher +1
As autonomous systems increasingly rely on Deep Neural Networks (DNN) to implement the navigation pipeline functions, uncertainty estimation methods have become paramount for estim…
Quantifying and Using System Uncertainty in UAV Navigation
Fabio Arnez, Ansgar Radermacher, Huascar Espinoza
As autonomous systems increasingly rely on Deep Neural Networks (DNN) to implement the navigation pipeline functions, uncertainty estimation methods have become paramount for estim…
Improving Robustness of Deep Neural Networks for Aerial Navigation by Incorporating Input Uncertainty
Fabio Arnez, Huascar Espinoza, Ansgar Radermacher +1
Uncertainty quantification methods are required in autonomous systems that include deep learning (DL) components to assess the confidence of their estimations. However, to successf…
A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications
Fabio Arnez, Huascar Espinoza, Ansgar Radermacher +1
A key factor for ensuring safety in Autonomous Vehicles (AVs) is to avoid any abnormal behaviors under undesirable and unpredicted circumstances. As AVs increasingly rely on Deep N…