| Issue Date | Title | Involved Person(s) |
| 2022 | A systematic overview on methods to protect sensitive data provided for various analyses | Templ, Matthias; Sariyar, Murat |
| 23-Sep-2021 | Statistical analysis of chemical element compositions in Food Science : problems and possibilities | Templ, Matthias; Templ, Barbara |
| 2021 | Artificial neural networks to impute rounded zeros in compositional data | Templ, Matthias |
| 2021 | Coincidence of temperature extremes and phenological events of grapevines | Templ, Barbara; Templ, Matthias; Barbieri, Roberto; Meier, Michael; Zufferey, Vivan |
| 2021 | Comparison of zero replacement strategies for compositional data with large numbers of zeros | Lubbe, Sugnet; Filzmoser, Peter; Templ, Matthias |
| 2021 | Can we ignore the compositional nature of compositional data by using deep learning aproaches? | Templ, Matthias |
| 18-Dec-2020 | Artificial neural networks to impute rounded zeros in compositional data | Templ, Matthias |
| 9-Nov-2020 | Anonymization and re-identification risk of personal data | Templ, Matthias |
| 7-Nov-2020 | Strategies to replace high proportions of zeros in compositional data | Filzmoser, Peter; Lubbe, Sugnet; Templ, Matthias |
| 6-Oct-2020 | Classical and robust regression analysis with compositional data | van den Boogaart, K.G.; Filzmoser, P.; Hron, K.; Templ, M.; Tolosano-Delgado, R. |
| 17-Jul-2020 | Preservation of individuals’ privacy in shared COVID-19 related data | Sauermann, Stefan; Kanjala, Chifundo; Templ, Matthias; Austin, Claire C. |
| Feb-2020 | Fleet management in free-floating bike sharing systems using predictive modelling and explorative tools | Templ, Matthias; Heitz, Christoph |
| 2020 | Anonymisierung von personenbezogenen Daten | Templ, Matthias |
| 2020 | Functional data analysis in Bayes spaces with an application to spatio-temporal population data | Templ, Matthias |
| 2020 | Exploratives Lernen mittels Fallen stellen, Fehler provozieren und Feedback geben | Templ, Matthias |
