paper-conference

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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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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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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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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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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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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