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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 |
| 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 |
| Jun-2015 | AI in Switzerland | Dessimoz, Jean-Daniel; Koehler, Jana; Stadelmann, Thilo |
| 14-Jun-2019 | Applied data science : lessons learned for the data-driven business | Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt |
| 2013 | Applied data science in Europe : challenges for academia in keeping up with a highly demanded topic | Stadelmann, Thilo; Stockinger, Kurt; Braschler, Martin; Cieliebak, Mark; Baudinot, Gerold, et al |
| Nov-2020 | Artificial neural networks in pattern recognition | Schilling, Frank-Peter; Stadelmann, Thilo |
| Sep-2020 | Artificial neural networks in pattern recognition : proceedings of the 9th IAPR TC3 workshop, ANNPR 2020, Winterthur, Switzerland, September 2–4, 2020 | Schilling, Frank-Peter; Stadelmann, Thilo |
| 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 |
| 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 |
| 14-Jun-2019 | Automated machine learning in practice : state of the art and recent results | Tuggener, Lukas; Amirian, Mohammadreza; Rombach, Katharina; Lörwald, Stefan; Varlet, Anastasia, et al |
| 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 |
| 14-Jun-2019 | Beyond ImageNet : deep learning in industrial practice | Stadelmann, Thilo; Tolkachev, Vasily; Sick, Beate; Stampfli, Jan; Dürr, Oliver |
| 27-Oct-2021 | Bias, awareness, and ignorance in deep-learning-based face recognition | Wehrli, Samuel; Hertweck, Corinna; Amirian, Mohammadreza; Glüge, Stefan; Stadelmann, Thilo |
| 2018 | Capturing suprasegmental features of a voice with RNNs for improved speaker clustering | Stadelmann, Thilo; Glinski-Haefeli, Sebastian; Gerber, Patrick; Dürr, Oliver |
| 31-Aug-2020 | Combining reinforcement learning with supervised deep learning for neural active scene understanding | Roost, Dano; Meier, Ralph; Toffetti Carughi, Giovanni; Stadelmann, Thilo |
| 10-Mar-2022 | Data centrism and the core of Data Science as a scientific discipline | Stadelmann, Thilo; Klamt, Tino; Merkt, Philipp H. |
| 2019 | Data products | Meierhofer, Jürg; Stadelmann, Thilo; Cieliebak, Mark |
| 14-Jun-2019 | Data science | Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt |
