| Issue Date | Title | Involved Person(s) |
| 15-Jun-2023 | Bias on demand : a modelling framework that generates synthetic data with bias | Baumann, Joachim; Castelnovo, Alessandro; Crupi, Riccardo; Inverardi, Nicole; Regoli, Daniele |
| 6-Jun-2023 | Wie integrieren wir KI in die berufliche und akademische Schreibpraxis? | Pernstich, Kurt; Messenzehl-Kölbl, Lisa |
| Jun-2023 | Physics-informed machine learning for predictive maintenance : applied use-cases | Goren Huber, Lilach; Palmé, Thomas; Arias Chao, Manuel |
| Jun-2023 | Video object detection for privacy-preserving patient monitoring in intensive care | Emberger, Raphael; Boss, Jens Michael; Baumann, Daniel; Seric, Marko; Huo, Shufan; Tuggener, Lukas; Keller, Emanuela; Stadelmann, Thilo |
| Jun-2023 | From concept to implementation : the data-centric development process for AI in industry | Luley, Paul-Philipp; Deriu, Jan Milan; Yan, Peng; Schatte, Gerrit A.; Stadelmann, Thilo |
| 26-Apr-2023 | Machine learning-based test selection for simulation-based testing of self-driving cars software | Birchler, Christian; Khatiri, Sajad; Bosshard, Bill; Gambi, Alessio; Panichella, Sebastiano |
| Apr-2023 | PID parameter tables after ITAE to control overshooting systems found with AI algorithm | Büchi, Roland |
| 30-Mar-2023 | Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks | Amirian, Mohammadreza; Montoya-Zegarra, Javier A.; Herzig, Ivo; Eggenberger Hotz, Peter; Lichtensteiger, Lukas; Morf, Marco; Züst, Alexander; Paysan, Pascal; Peterlik, Igor; Scheib, Stefan; Füchslin, Rudolf Marcel; Stadelmann, Thilo; Schilling, Frank-Peter |
| Mar-2023 | Deep learning super resolution for high-speed excitation emission matrix measurements | Michelucci, Umberto; Fluri, Silvan; Baumgartner, Michael; Venturini, Francesca |
| Mar-2023 | Understanding the learning mechanism of convolutional neural networks applied to fluorescence spectra | Venturini, Francesca; Michelucci, Umberto; Sperti, Michela; Gucciardi, Arnaud; Deriu, Marco A. |
| 1-Feb-2023 | Understanding the learning mechanism of convolutional neural networks applied to fluorescence spectra | Venturini, Francesca; Michelucci, Umberto; Sperti, Michela; Gucciardi, Arnaud; Deriu, Marco A. |
| Feb-2023 | Deconvolution of 1D NMR spectra : a deep learning-based approach | Schmid, N.; Bruderer, S.; Paruzzo, F.; Fischetti, G.; Toscano, G.; Graf, D.; Fey, M.; Henrici, A.; Ziebart, V.; Heitmann, B.; Grabner, H.; Wegner, J.D.; Sigel, R.K.O.; Wilhelm, D. |
| 11-Jan-2023 | certAInty : a certification scheme for AI systems (Innosuisse project) | Weng, Joanna; Reif, Monika; Chavarriaga, Ricardo; Schilling, Frank-Peter |
| 11-Jan-2023 | Deep learning the SKA : the Square Kilometer Array project | Denzel, Philipp Benedikt; Schilling, Frank-Peter; Gavagnin, Elena |
| 11-Jan-2023 | Deconvolution of NMR spectra : a deep learning-based approach | Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe; Graf, Dominik; Fey, Michael; Ziebart, Volker; Henrici, Andreas; Grabner, Helmut; Wegner, Jan Dirk; Sigel, Roland K.O.; Heitmann, Björn; Wilhelm, Dirk |
