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| Issue Date | Title | Involved Person(s) |
| 2-Jan-2024 | A comprehensive survey of deep transfer learning for anomaly detection in industrial time series : methods, applications, and directions | Yan, Peng; Abdulkadir, Ahmed; Luley, Paul-Philipp; Rosenthal, Matthias; Schatte, Gerrit A., et al |
| 2-Nov-2023 | A framework for assessing and certifying explainability of health-oriented AI systems | Denzel, Philipp; Brunner, Stefan; Luley, Paul-Philipp; Frischknecht-Gruber, Carmen; Reif, Monika Ulrike, et al |
| 9-Jun-2021 | A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applications | Simmler, Niclas; Sager, Pascal; Andermatt, Philipp; Chavarriaga, Ricardo; Schilling, Frank-Peter, et al |
| 22-Apr-2022 | A theory of natural intelligence | von der Malsburg, Christoph; Stadelmann, Thilo; Grewe, Benjamin F. |
| Jun-2022 | Advances in deep neural networks for visual pattern recognition | Stadelmann, Thilo; Schilling, Frank-Peter |
| Nov-2021 | Are we summarizing the right way? : a survey of dialogue summarization data sets | Tuggener, Don; Mieskes, Margot; Deriu, Jan Milan; Cieliebak, Mark |
| Jan-2024 | Artifact reduction in 3D and 4D cone-beam computed tomography images with deep learning - a review | Amirian, Mohammadreza; Barco, Daniel; Herzig, Ivo; Schilling, Frank-Peter |
| Nov-2020 | Artificial neural networks in pattern recognition | Schilling, Frank-Peter; Stadelmann, Thilo |
| 21-Dec-2023 | Assessing deep learning : a work program for the humanities in the age of artificial intelligence | Segessenmann, Jan; Stadelmann, Thilo; Davison, Andrew; Dürr, Oliver |
| 28-Aug-2023 | Assessing deep learning : a work program for the humanities in the age of artificial intelligence | Segessenman, Jan; Stadelmann, Thilo; Andrew, Davison; Oliver, Dürr |
| 31-May-2024 | Automated process monitoring in injection molding via representation learning and setpoint regression | Yan, Peng; Abdulkadir, Ahmed; Aguzzi, Giulia; Schatte, Gerrit A.; Grewe, Benjamin F., et al |
| 27-Oct-2021 | Bias, awareness, and ignorance in deep-learning-based face recognition | Wehrli, Samuel; Hertweck, Corinna; Amirian, Mohammadreza; Glüge, Stefan; Stadelmann, Thilo |
| 11-Jan-2023 | certAInty : a certification scheme for AI systems (Innosuisse project) | Weng, Joanna; Reif, Monika; Chavarriaga, Ricardo; Schilling, Frank-Peter |
| 2023 | Correction of errors in preference ratings from automated metrics for text generation | Deriu, Jan; von Däniken, Pius; Tuggener, Don; Cieliebak, Mark |
| 16-Dec-2021 | Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials | Batzianoulis, Iason; Iwane, Fumiaki; Wei, Shupeng; Correia, Carolina Gaspar Pinto Ramos; Chavarriaga, Ricardo, et al |
| 22-Feb-2024 | Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction | Iwane, Fumiaki; Porssut, Thibault; Blanke, Olaf; Chavarriaga, Ricardo; Millan, Jose Del R., et al |
| 10-Mar-2022 | Data centrism and the core of Data Science as a scientific discipline | Stadelmann, Thilo; Klamt, Tino; Merkt, Philipp H. |
| 2023 | Deep ensemble inverse model for image-based estimation of solar cell parameters | Battaglia, Mattia; Comi, Ennio; Stadelmann, Thilo; Hiestand, Roman; Ruhstaller, Beat, et al |
| 2023 | Deep learning for robust and explainable models in computer vision | Schwenker, Friedhelm; Stadelmann, Thilo; Jaggi, Martin; Amirian, Mohammadreza |
| 11-Jan-2023 | Deep learning the SKA : the Square Kilometer Array project | Denzel, Philipp Benedikt; Schilling, Frank-Peter; Gavagnin, Elena |
