51 citations · 53 across the 5 of their papers we have counts for
6 papers
When do World Models Successfully Learn Dynamical Systems?
Edmund Ross, Claudia Drygala, Leonhard Schwarz +4
In this work, we explore the use of compact latent representations with learned time dynamics ('World Models') to simulate physical systems. Drawing on concepts from control theory…
Learning Brenier Potentials with Convex Generative Adversarial Neural Networks
Claudia Drygala, Hanno Gottschalk, Thomas Kruse +2
Brenier proved that under certain conditions on a source and a target probability measure there exists a strictly convex function such that its gradient is a transport map from the…
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…
Generalization capabilities of conditional GAN for turbulent flow under changes of geometry
Claudia Drygala, Francesca di Mare, Hanno Gottschalk
Turbulent flow consists of structures with a wide range of spatial and temporal scales which are hard to resolve numerically. Classical numerical methods as the Large Eddy Simulati…
Generative Modeling of Turbulence
Claudia Drygala, Benjamin Winhart, Francesca di Mare +1
We present a mathematically well founded approach for the synthetic modeling of turbulent flows using generative adversarial networks (GAN). Based on the analysis of chaotic, deter…
Background-Foreground Segmentation for Interior Sensing in Automotive Industry
Claudia Drygala, Matthias Rottmann, Hanno Gottschalk +2
To ensure safety in automated driving, the correct perception of the situation inside the car is as important as its environment. Thus, seat occupancy detection and classification…