| Issue Date | Title | Involved Person(s) |
| 15-Jun-2024 | Bayesian analysis of 1D 1H-NMR spectra | De Lorenzi, Flavio; Weinmann, Tom; Bruderer, Simon; Heitmann, Björn; Henrici, Andreas, et al |
| 15-Aug-2023 | Editorial: Artificial Intelligence in Finance and Industry: volume II—highlights from the 7th European conference | Henrici, Andreas; Füchslin, Rudolf M.; Schwendner, Peter |
| Jul-2023 | Transforming NMR spectroscopy : extraction of multiplet parameters with deep learning | Schmid, Nicolas; Fischetti, Giulia; Henrici, Andreas; Wilhelm, Dirk; Wanner, Marc, et al |
| Jul-2023 | Uncertainty quantification for reliable automatic multiplet classification in 1H NMR spectra | Fischetti, Giulia; Schmid, Nicolas; Henrici, Andreas; Wilhelm, Dirk; Bruderer, Simon, et al |
| Feb-2023 | Deconvolution of 1D NMR spectra : a deep learning-based approach | Schmid, N.; Bruderer, S.; Paruzzo, F.; Fischetti, G.; Toscano, G., et al |
| 11-Jan-2023 | Deconvolution of NMR spectra : a deep learning-based approach | Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe, et al |
| 11-Jan-2023 | Automatic classification of signal regions in 1H nuclear magnetic resonance spectra | Fischetti, Giulia; Schmid, Nicolas; Bruderer, Simon; Caldarelli, Guido; Scarso, Alessandro, et al |
| 9-Sep-2022 | Editorial: Artificial intelligence in finance and industry: highlights from 6 European COST conferences | Henrici, Andreas; Osterrieder, Jörg |
| 14-Jul-2022 | A deep ensemble learning method for automatic classification of multiplets in 1D NMR spectra | Fischetti, Giulia; Schmid, Nicolas; Bruderer, Simon; Paruzzo, Federico; Toscano, Giuseppe, et al |
| 13-Jul-2022 | Deconvolution of NMR spectra : a deep learning-based approach | Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe, et al |
