3 papers
cs.LG2026
Generative Adversarial Learning from Deterministic Processes
Joris C. Kühl, Hanno Gottschalk
Physical AI is being successfully applied to data which does not follow the traditional paradigm of independent and identically distributed (i.i.d.) samples. In fact, physical AI i…
physics.flu-dyn2026
Learning Transient Convective Heat Transfer with Geometry Aware World Models
Onur T. Doganay, Alexander Klawonn, Martin Eigel +1
Partial differential equation (PDE) simulations are fundamental to engineering and physics but are often computationally prohibitive for real-time applications. While generative AI…
cs.LG2025
Robust Evolutionary Multi-Objective Network Architecture Search for Reinforcement Learning (EMNAS-RL)
Nihal Acharya Adde, Alexandra Gianzina, Hanno Gottschalk +1
This paper introduces Evolutionary Multi-Objective Network Architecture Search (EMNAS) for the first time to optimize neural network architectures in large-scale Reinforcement Lear…