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Unlocking the potential of unlabeled data: Self-supervised machine learning for battery aging diagnosis with real-world field data2024 Journal of Energy Chemistry article Engineering Advanced Battery Technologies Research Open access
Qiao Wang, Min Ye, Sehriban Celik, Zhongwei Deng, Bin Li, Dirk Uwe Sauer, +1 more
32citations -
The potential of deep learning to reduce complexity in energy system modeling2021 International Journal of Energy Research article Engineering Integrated Energy Systems Optimization Open access
Clara Sophie Köhnen, Jan Priesmann, Lars Nolting, Leander Kotzur, Martin Robinius, Aaron Praktiknjo
15citations -
Identifying and Analyzing Data Model Requirements and Technology Potentials of Machine Learning Systems in the Manufacturing Industry of the Future7citations
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Framework for Potential Analysis by Approximating Line-Less Assembly Systems with AutoML2021 Lecture notes in mechanical engineering conference-paper Engineering Flexible and Reconfigurable Manufacturing Systems
Lea Kaven, Jonas Rachner, Amon Göppert, Sazvan Saeed, Robert Heinrich Schmitt
5citations -
Identification and Characterization of Challenges in the Future of Manufacturing for the Application of Machine Learning8citations
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Task space adaptation via the learning of gait controllers of magnetic soft millirobots2021 The International Journal of Robotics Research article Engineering Soft Robotics and Applications Open access cited by 1 patent
Sinan Özgün Demir, Utku Çulha, Alp Can Karacakol, Abdon Pena‐Francesch, Sebastian Trimpe, Metin Sitti
33citations -
Interacting Federated and Transfer Learning-Aided CSI Prediction for Intelligent Cellular Networks2023 IEEE Transactions on Vehicular Technology article Engineering Advanced MIMO Systems Optimization cited by 1 patent
Jinlong Sun, Yibin Zhang, Guan Gui, Haitao Zhao, Haris Gacanin, Hikmet Sari
13citations -
Optimized Pulse Patterns Design for Electrical Drives: A Reinforcement Learning Approach2026 IEEE Open Journal of the Industrial Electronics Society article Engineering Electric Motor Design and Analysis Open access
Mohammad Abu-Ali, Felix Berkel, Maximilian Manderla, Markus Pietschner, Daniel Görges
0citations