activity
20242026
collaborators

13 papers

cs.AI2026

Multi-Agent Causal Reasoning System for Error Pattern Rule Automation in Vehicles

Hugo Math, Julian Lorenz, Stefan Oelsner +1

Modern vehicles generate thousands of different discrete events known as Diagnostic Trouble Codes (DTCs). Automotive manufacturers use Boolean combinations of these codes, called e…

cs.AI2026

Transforming Vehicle Diagnostics: A Multimodal Approach to Error Patterns Prediction

Hugo Math, Rainer Lienhart

Accurately diagnosing and predicting vehicle malfunctions is crucial for maintenance and safety in the automotive industry. While modern diagnostic systems primarily rely on sequen…

cs.CV2025

Uplifting Table Tennis: A Robust, Real-World Application for 3D Trajectory and Spin Estimation

Daniel Kienzle, Katja Ludwig, Julian Lorenz +2

Obtaining the precise 3D motion of a table tennis ball from standard monocular videos is a challenging problem, as existing methods trained on synthetic data struggle to generalize…

cs.CV2025

MMMS: Multi-Modal Multi-Surface Interactive Segmentation

Robin Schön, Julian Lorenz, Katja Ludwig +2

In this paper, we present a method to interactively create segmentation masks on the basis of user clicks. We pay particular attention to the segmentation of multiple surfaces that…

cs.LG2025

One-Shot Multi-Label Causal Discovery in High-Dimensional Event Sequences

Hugo Math, Robin Schön, Rainer Lienhart

Understanding causality in event sequences with thousands of sparse event types is critical in domains such as healthcare, cybersecurity, or vehicle diagnostics, yet current method…

cs.LG2025

Towards Practical Multi-label Causal Discovery in High-Dimensional Event Sequences via One-Shot Graph Aggregation

Hugo Math, Rainer Lienhart

Understanding causality in event sequences where outcome labels such as diseases or system failures arise from preceding events like symptoms or error codes is critical. Yet remain…