| Issue Date | Title | Involved Person(s) |
| Aug-2023 | New metric formulas that include measurement errors in machine learning for natural sciences | Michelucci, Umberto; Venturini, Francesca |
| 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 |
| Jul-2023 | Transforming NMR spectroscopy : extraction of multiplet parameters with deep learning | Schmid, Nicolas; Fischetti, Giulia; Henrici, Andreas; Wilhelm, Dirk; Wanner, Marc, et al |
| 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. |
| Feb-2023 | Deconvolution of 1D NMR spectra : a deep learning-based approach | Schmid, N.; Bruderer, S.; Paruzzo, F.; Fischetti, G.; Toscano, G., et al |
| 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. |
| 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 |
| 11-Jan-2023 | Deconvolution of NMR spectra : a deep learning-based approach | Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe, et al |
| 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 |
| 22-Jan-2020 | Applications of ML to oxygen sensing | Venturini, Francesca |
