2 citations · 7 across the 19 of their papers we have counts for
9 papers · 1 filter
Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
Julius Aka, Johannes Brunnemann, Jörg Eiden +2
Variational Autoencoders (VAEs) are a powerful framework for learning latent representations of reduced dimensionality, while Neural ODEs excel in learning transient system dynamic…
GeoBiked: A Dataset with Geometric Features and Automated Labeling Techniques to Enable Deep Generative Models in Engineering Design
Phillip Mueller, Sebastian Mueller, Lars Mikelsons
We provide a dataset for enabling Deep Generative Models (DGMs) in engineering design and propose methods to automate data labeling by utilizing large-scale foundation models. GeoB…
Perspectives-Observer-Transparency -- A Novel Paradigm for Modelling the Human in Human-To-Anything Interaction Based on a Structured Review of the Human Digital Twin
Nils Mandischer, Alexander Atanasyan, Michael Schluse +2
Modern modelling approaches fail when it comes to understanding rather than pure supervision of human behavior. As humans become more and more integrated into human-to-anything int…
Exploring Capability-Based Control Distributions of Human-Robot Teams Through Capability Deltas: Formalization and Implications
Nils Mandischer, Marcel Usai, Frank Flemisch +1
The implicit assumption that human and autonomous agents have certain capabilities is omnipresent in modern teaming concepts. However, none formalize these capabilities in a flexib…
InsertDiffusion: Identity Preserving Visualization of Objects through a Training-Free Diffusion Architecture
Phillip Mueller, Jannik Wiese, Ioan Craciun +1
Recent advancements in image synthesis are fueled by the advent of large-scale diffusion models. Yet, integrating realistic object visualizations seamlessly into new or existing ba…
Exploring the Potentials and Challenges of Deep Generative Models in Product Design Conception
Phillip Mueller, Lars Mikelsons
The synthesis of product design concepts stands at the crux of early-phase development processes for technical products, traditionally posing an intricate interdisciplinary challen…