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cs.LG2025
Masked Conditioning for Deep Generative Models
Phillip Mueller, Jannik Wiese, Sebastian Mueller +1
Datasets in engineering domains are often small, sparsely labeled, and contain numerical as well as categorical conditions. Additionally. computational resources are typically limi…
cs.LG2025
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…