collaborators

6 papers

cs.LG2026

Have I Solved This Before? Retrieving Similar Segmentation Problems for Evolutionary Learning

Andreas Margraf, Henning Cui, Jörg Hähner

Reliable integration and solid configuration of monitoring systems constitute a fundamental prerequisites for achieving high efficiency and productivity in contemporary manufacturi…

cs.NE2026

Performance and Explainability Requirements of Evolutionary Algorithms in Real-World Physics-Informed Optimization

Helena Stegherr, Michael Heider, Nils Meyer +7

Evolutionary computation offers a variety of tools to solve complex real-world optimization problems. However, research often focuses on smaller, simplified problems and optimizati…

cs.AI2026

Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation

Roman Küble, Marco Hüller, Mrunmai Phatak +2

Semantic world models enable embodied agents to reason about objects, relations, and spatial context beyond purely geometric representations. In Organic Computing, such models are…

cs.LG2026

Unsupervised Anomaly Detection in Process-Complex Industrial Time Series: A Real-World Case Study

Sergej Krasnikov, Lukas Meitz, Samineh Bagheri +3

Industrial time-series data from real production environments exhibits substantially higher complexity than commonly used benchmark datasets, primarily due to heterogeneous, multi-…

cs.NE2026

Pareto-Optimal Anytime Algorithms via Bayesian Racing

Jonathan Wurth, Helena Stegherr, Neele Kemper +2

Selecting an optimization algorithm requires comparing candidates across problem instances, but the computational budget for deployment is often unknown at benchmarking time. Curre…

cs.CV2025

HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions

Mrunmai Vivek Phatak, Julian Lorenz, Nico Hörmann +2

When humans and robotic agents coexist in an environment, scene understanding becomes crucial for the agents to carry out various downstream tasks like navigation and planning. Hen…