3 papers
cs.SE2026
Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verification
Simos Gerasimou, Xingyu Zhao
Combining Bayesian learning and quantitative verification is a powerful toolset for analysing key quantitative properties of software systems, like reliability and response time. H…
cs.SE2025
On the Need for a Statistical Foundation in Scenario-Based Testing of Autonomous Vehicles
Xingyu Zhao, Robab Aghazadeh-Chakherlou, Chih-Hong Cheng +2
Scenario-based testing has emerged as a common method for autonomous vehicles (AVs) safety assessment, offering a more efficient alternative to mile-based testing by focusing on hi…
cs.CV2025
Risk Controlled Image Retrieval
Kaiwen Cai, Chris Xiaoxuan Lu, Xingyu Zhao +1
Most image retrieval research prioritizes improving predictive performance, often overlooking situations where the reliability of predictions is equally important. The gap between…