activity
20242026
collaborators

24 papers

cs.CV2026

Extended Field of View Analysis for VideoGAN-based Trajectory Generation

Annajoyce Mariani, Kira Maag, Hanno Gottschalk

Realistic and diverse trajectory generation is central to enabling higher levels of vehicle automation. While rule-based and classical learning-based methods may struggle to captur…

cs.AI2026

Generative Design of a Gas Turbine Combustor Using Invertible Neural Networks

Patrick Krüger, Hanno Gottschalk, Werner Krebs +1

The need to burn 100% H2 in high efficient gas turbines featuring low NOx combustion in premix mode require the complete redesign of the combustion system to ensure stable operatio…

cs.CV2026

Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection

Tobias J. Riedlinger, Kira Maag, Hanno Gottschalk

Deep neural networks have set the state-of-the-art in computer vision tasks such as bounding box detection and semantic segmentation. Object detectors and segmentation models assig…

cs.LG2026

How well do generative models solve inverse problems? A benchmark study

Patrick Krüger, Patrick Materne, Werner Krebs +1

Generative learning generates high dimensional data based on low dimensional conditions, also called prompts. Therefore, generative learning algorithms are eligible for solving (Ba…

cs.LG2026

Generative Design of Ship Propellers using Conditional Flow Matching

Patrick Kruger, Rafael Diaz, Simon Hauschulz +2

In this paper, we explore the use of generative artificial intelligence (GenAI) for ship propeller design. While traditional forward machine learning models predict the performance…

physics.flu-dyn2026

Comparison of Generative Learning Methods for Turbulence Surrogates

Claudia Drygala, Edmund Ross, Mohammad Sharifi Ghazijahani +3

Numerical simulations of turbulent flows present significant challenges in fluid dynamics due to their complexity and high computational cost. High resolution techniques such as Di…