48 citations · 71 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning
Nihal Acharya Adde, Hanno Gottschalk, Andreas Ebert
This paper focuses on hyperparameter optimization for autonomous driving strategies based on Reinforcement Learning. We provide a detailed description of training the RL agent in a…
Uncertainty quantification for damage mechanics models using the bootstrap method
Mohamed Saadi, Felix Kölzow, Christian Kontermann +2
We quantify the uncertainty of the Lämmer model of damage evolution when fitted to (noisy) observations of damage evolution in cyclic fatigue experiments with and without dwell tim…
Optimal control of thermal and mechanical loads in activation processes of mechanical components
Nicolai Friedlich, Hanno Gottschalk, Georg Vossen
This paper develops a mathematical framework that aims to control the temperature and rotational speed in the activation process of a gas turbine in an optimal way. These controls…
Modeling, Minimizing and Managing the Risk of Fatigue for Mechanical Components
L. Bittner, H. Gottschalk, M. Gröger +3
Mechanical components that are exposed to cyclic mechanical loading fail at loads that are well below the ultimate tensile strength. This process is known as fatigue. The failure t…
Assessment of Models for Pedestrian Dynamics with Functional Principal Component Analysis
M. Chraibi, T. Ensslen, H. Gottschalk +2
Many agent based simulation approaches have been proposed for pedestrian flow. As such models are applied e.g.\ in evacuation studies, the quality and reliability of such models is…
Systems of classical particles in the grand canonical ensemble, scaling limits and quantum field theory
S. Albeverio, H. Gottschalk, M. W. Yoshida
Euclidean quantum fields obtained as solutions of stochastic partial pseudo differential equations driven by a Poisson white noise have paths given by locally integrable functions.…
Models of local relativistic quantum fields with indefinite metric (in all dimensions)
S. Albeverio, H. Gottschalk, J. -L. Wu
A condition on a set of truncated Wightman functions is formulated and shown to permit the construction of the Hilbert space structure included in the Morchio--Strocchi modified Wi…