Publications
62 publications from the first funding phase, from journal articles on composite forming to machine learning conference papers. Names of Research Unit members are set in bold.
2026 21
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Adaptive Swarm Mesh Refinement using Deep Reinforcement Learning with Local Rewards
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Context-aware Learned Mesh-based Simulation via Trajectory-Level Meta-Learning
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Planning-Based Decision Space Exploration for Digital Twins in Immature Production Processes
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Adaptive Sequential Sensor Placement for Robust and Efficient Online Fault Diagnosis
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Bayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods
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Gaussian Homotopy Optimization with Predictor–Corrector Path Tracking and Deterministic Sampling
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Improving Long-Range Interactions in Graph Neural Simulators via Hamiltonian Dynamics
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LLM-Based Pre-Press Decision Support for an Industrial Composite-Forming Workflow
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Local Modified Cramér–von Mises Distance for Uncertainty Calibration Assessment in Regression
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Long-Range Spatio-Temporal Graph Propagation Through Oscillations
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Point Cloud Sequence Encoding for Material-conditioned Graph Network Simulators
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Smooth Sampling-Based Model Predictive Control Using Deterministic Samples
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Development and validation of a modular and over-instrumented gripper frame for the handling and thermoforming of UD fiber-reinforced thermoplastic tape laminates
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BOING: Optimizing Bayesian Optimization with Information Geometry
2025 21
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3D solid-shell element for macroscopic composite forming simulation enabling thickness prediction
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AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction
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Causal Temporal Neural Networks Using the Conditional Average Treatment Effect
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Diffusion-Based Hierarchical Graph Neural Networks for Simulating Nonlinear Solid Mechanics
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Evaluating the Performance of RAG Methods for Conversational AI in the Airport Domain
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Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects
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Local Calibration Testing in Supervised Machine Learning Models Using Input Space Kernels
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MaNGO – Adaptable Graph Network Simulators via Meta-Learning
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Weaknesses of the ANEES and New Calibration Measures for Multivariate Predictions
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Towards a Generalised Information Modell: A Bayesian Network Approach for PPR-Representation
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Bayesian Optimization using Partially Observable Gaussian Process Network
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Towards Using the Solid Protocol for Data Transport in International Data Spaces (IDS)
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Workshop Report: Learning Approaches for Hybrid Dynamical Systems
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Process simulation data for thermoforming of continuous fiber-reinforced composite materials
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Newton-Flow Particle Filters based on Generalized Cramér Distance
2024 11
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Towards Representing Processes and Reasoning with Process Descriptions on the Web
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Considering the viscoelastic material behavior in a solid-shell element for thermoforming simulation
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Joint parameter and state-space modelling of manufacturing processes using Gaussian processes
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Metrics for the Evaluation of Learned Causal Graphs Based on Ground Truth
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Multi-Scale Uncertainty Calibration Testing for Bayesian Neural Networks Using Ball Trees
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Root Cause Analysis Using Anomaly Detection and Temporal Informed Causal Graphs
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Voronoi Trust Regions for Local Calibration Testing in Supervised Machine Learning Models
2023 9
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Causal Structure Learning Using PCMCI+ and Path Constraints from Wavelet-Based Soft Interventions
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Counterfactual Root Cause Analysis via Anomaly Detection and Causal Graphs
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Grounding Graph Network Simulators using Physical Sensor Observations
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Progressive Bayesian Particle Flows Based on Optimal Transport Map Sequences
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