Publications

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Pointwise-in-Time Diagnostics for Reinforcement Learning during Training and Runtime
A framework for explaining RL agents during training and runtime based the definition of an agents desired behavior through linear temporal logic (LTL).
Noel Brindise, Andres Felipe Posada-Moreno, Cedric Langbort, Sebastian Trimpe
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ECLAD: Extracting Concepts with Local Aggregated Descriptors
A novel method for automatic concept extraction and localization based on representations obtained through pixel-wise aggregations of CNN activation maps.
Andres Felipe Posada-Moreno, Nikita Surya, Sebastian Trimpe
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Scale-Preserving Automatic Concept Extraction (SPACE)
We introduce the Scale-Preserving Automatic Concept Extraction (SPACE) algorithm, as a state-of-the-art alternative concept extraction technique for CNNs, focused on industrial applications.
Andres Felipe Posada-Moreno, Lukas Kreisköther, Tassilo Glander, Sebastian Trimpe
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Scalable Concept Extraction in Industry 4.0
Applying concept extraction (ECLAD) for explaining CNNs in industrial use cases.
Andres Felipe Posada-Moreno, Kai Müller, Florian Brillowski, Friedrich Solowjow, Thomas Gries, Sebastian Trimpe
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Process Parameter Prediction for Fused Deposition Modeling Using Invertible Neural Networks
Process Parameter Prediction for Fused Deposition Modeling Using Invertible Neural Networks.
Lukas Pelzer, Andres Felipe Posada-Moreno, Kai Müller, Christoph Greb, Christian Hopmann
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Objectifying Machine Setup and Parameter Selection in Expert Knowledge Dependent Industries Using Invertible Neural Networks
Using invertible neural networks and expert knowledge for parameter prediction in industrial applications.
Kai Müller, Andrés Posada-Moreno, Lukas Pelzer, Thomas Gries
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Actionable Artificial Intelligence for the Future of Production
Compilation of fundamentals and applications of AI and data based systems in the context of the Industry 4.0.
Mohamed Behery, Philipp Brauner, Hans Aoyang Zhou, Merih Seran Uysal, Vladimir Samsonov, Martin Bellgardt, Florian Brillowski, Tobias Brockhoff, Anahita Farhang Ghahfarokhi, Lars Gleim, Leon Michel Gorissen, Marco Grochowski, Thomas Henn, Elisa Iacomini, Thomas Kaster, István Koren, Martin Liebenberg, Leon Reinsch, Liam Tirpitz, Minh Trinh, Andres Felipe Posada-Moreno, Luca Liehner, Thomas Schemmer, Luisa Vervier, Marcus Völker, Philipp Walderich, Song Zhang, Christian Brecher, Robert H. Schmitt, Stefan Decker, Thomas Gries, Constantin Leon Häfner, Michael Herty, Matthias Jarke, Stefan Kowalewski, Torsten W. Kuhlen, Johannes Henrich Schleifenbaum, Sebastian Trimpe, Wil M. P. van der Aalst, Martina Ziefle, Gerhard Lakemeyer
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Towards Cargo Wagons Brake Health Scoring through Image Processing.
This publication presents a system for the automated scoring of cargo wagon brakes through image processing and deep learning algorithms.
Andres Felipe Posada-Moreno, Thomas Otte, Damir Pehar, Marc Haßler, Holger Bartels, Anas Abdelrazeq, Frank Hees
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Condition Monitoring of Rail Infrastructure and Rolling Stock Using Acceleration Sensor Data of On-Rail Freight Wagons.
Methods to monitor the condition of the existing rail infrastructure as well as the rolling stock by obtaining insights from raw sensor data.
Thomas Otte, Andres Felipe Posada-Moreno, Fabian Hübenthal, Marc Haßler, Holger Bartels, Anas Abdelrazeq, Frank Hees
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Neural-Network-based State Estimation: The Effect of Pseudo- Measurements
Tackling the problem of state estimation in power systems using Deep learning models.
Andrea Bragantini, Davide Baroli, Andres Felipe Posada-Moreno, Andrea Benigni
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Transfer of Hierarchical Reinforcement Learning Structures for Robotic Manipulation Tasks
In this paper we investigate the possibility of reusing low-level policies to improve training efficiency when learning manipulation tasks with an industrial robot.
Christian Scheiderer, Malte Mosbach, Andres Felipe Posada-Moreno, Tobias Meisen
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Simulation-as-a-Service for Reinforcement Learning Applications by Example of Heavy Plate Rolling Processes
In this paper we propose a distributed architecture which allows the remote training of reinforcement learning agents on a simulation.
Christian Scheiderer, Timo Thun, Christian Idzik, Andres Felipe Posada-Moreno, Alexander Krämer, Johannes Lohmar, Gerhard Hirt, Tobias Meisen
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Holistic Data Infrastructure and Analytics System for Rail Freight Transport
Introduction of a holistic data infrastructure and analytics framework for the improvement of rail freight transport systems. In collaboration with Deutsche Bahn.
Thomas Otte, Holger Bartels, Andres Felipe Posada-Moreno, Georg Wittenburg, Marc Haßler
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Cargo Wagon Structural Health Estimation Using Computer Vision
This publication describes a vision of a support system for wagon health assessment. In collaboration with DB Cargo.
A. F. Posada-Moreno, C. Klein, M. Haßler, D. Pehar, A. F. Solvay, C. P. Kohlschein
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