2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Diffusion-Based Generation and Imputation of Driving Scenarios from Limited Vehicle CAN Data
Julian Ripper, Ousama Esbel, Rafael Fietzek +2
Training deep learning methods on small time series datasets that also include corrupted samples is challenging. Diffusion models have shown to be effective to generate realistic a…
cs.LG2023★ 2 cited
Unsupervised Driving Event Discovery Based on Vehicle CAN-data
Thomas Kreutz, Ousama Esbel, Max Mühlhäuser +1
The data collected from a vehicle's Controller Area Network (CAN) can quickly exceed human analysis or annotation capabilities when considering fleets of vehicles, which stresses t…