17 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Technical University of MunichDE3 papers
- ift RosenheimDE2 papers
- Berlin School of Economics and LawDE1 paper
- Deutsches ForschungsnetzDE1 paper
- Georg Simon Ohm University of Applied Sciences NurembergDE1 paper
- Otto-von-Guericke-Universität MagdeburgDE1 paper
- Robert Bosch (Germany)DE1 paper
- Siemens (Germany)DE1 paper
- University of AugsburgDE1 paper
14 papers
Curriculum Learning with GNN-based Reinforcement Learning for Job Shop Scheduling
Jayakrishnan K. Vasudevan, Jonathan Hoss, Noah Klarmann
The job shop scheduling problem is a challenging combinatorial optimization problem, and recent reinforcement learning approaches using graph neural networks have shown promise for…
Multilingual Stutter Event Detection for English, German, and Mandarin Speech
Felix Haas, Sebastian P. Bayerl
This paper presents a multi-label stuttering detection system trained on multi-corpus, multilingual data in English, German, and Mandarin.By leveraging annotated stuttering data fr…
Advancements in synthetic data extraction for industrial injection molding
Georg Rottenwalter, Marcel Tilly, Christian Bielenberg +1
Machine learning has significant potential for optimizing various industrial processes. However, data acquisition remains a major challenge as it is both time-consuming and costly.…
Improving Industrial Injection Molding Processes with Explainable AI for Quality Classification
Georg Rottenwalter, Marcel Tilly, Victor Owolabi
Machine learning is an essential tool for optimizing industrial quality control processes. However, the complexity of machine learning models often limits their practical applicabi…
Prompt-Hacking: The New p-Hacking?
Thomas Kosch, Sebastian Feger
As Large Language Models (LLMs) become increasingly embedded in empirical research workflows, their use as analytical tools for quantitative or qualitative data raises pressing con…
GenTL: A General Transfer Learning Model for Building Thermal Dynamics
Fabian Raisch, Thomas Krug, Christoph Goebel +1
Transfer Learning (TL) is an emerging field in modeling building thermal dynamics. This method reduces the data required for a data-driven model of a target building by leveraging…
On an Interaction Model of General Language Change
Alfred Fuchs, Martin Schwingenheuer, Elisabeth Steinegger +1
In the following article, we construct an interaction model (a variant of the SIR-model) of general language change. In the context of language change it is desirable to deduce the…
Risk or Chance? Large Language Models and Reproducibility in HCI Research
Thomas Kosch, Sebastian Feger
Reproducibility is a major concern across scientific fields. Human-Computer Interaction (HCI), in particular, is subject to diverse reproducibility challenges due to the wide range…
DiAReL: Reinforcement Learning with Disturbance Awareness for Robust Sim2Real Policy Transfer in Robot Control
Mohammadhossein Malmir, Josip Josifovski, Noah Klarmann +1
Delayed Markov decision processes (DMDPs) fulfill the Markov property by augmenting the state space of agents with a finite time window of recently committed actions. In reliance o…
Analysis of Randomization Effects on Sim2Real Transfer in Reinforcement Learning for Robotic Manipulation Tasks
Josip Josifovski, Mohammadhossein Malmir, Noah Klarmann +3
Randomization is currently a widely used approach in Sim2Real transfer for data-driven learning algorithms in robotics. Still, most Sim2Real studies report results for a specific r…
On Langmuir's periodic orbit
Kai Cieliebak, Urs Frauenfelder, Martin Schwingenheuer
Niels Bohr successfully predicted in 1913 the energy levels for the hydrogen atom by applying certain quantization rules to classically obtained periodic orbits. Many physicists tr…
SQUADfps: Integrated Model-Based Machine Safety and Product Quality for Flexible Production Systems
Chee Hung Koo, Stefan Rothbauer, Marian Vorderer +2
Growing individualization of products up to lot-size-1 and high volatility of product mixes lead to new challenges in the manufacturing domain, including the need for frequent reco…
Timage -- A Robust Time Series Classification Pipeline
Marc Wenninger, Sebastian P. Bayerl, Jochen Schmidt +1
Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of rese…
Selection theory of free dendritic growth in a potential flow
Martin von Kurnatowski, Thomas Grillenbeck, Klaus Kassner
The Kruskal-Segur approach to selection theory in diffusion-limited or Laplacian growth is extended via combination with the Zauderer decomposition scheme. This way nonlinear bulk…