| Significance of patterns in data visualisations R Savvides, A Henelius, E Oikarinen, K Puolamäki Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 10 | 2019 |
| Interactive Causal Structure Discovery in Earth System Sciences L Melkas, R Savvides, SH Chandramouli, J Mäkelä, T Nieminen, ... The KDD'21 Workshop on Causal Discovery, 3-25, 2021 | 9 | 2021 |
| Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets M Lange, H Suominen, M Kurppa, L Järvi, E Oikarinen, R Savvides, ... Geoscientific Model Development 14 (12), 7411-7424, 2021 | 6 | 2021 |
| Finding statistically significant high accident counts in exploration of occupational accident data T Räsänen, A Reiman, K Puolamäki, R Savvides, E Oikarinen, E Lantto Journal of safety research 82, 28-37, 2022 | 3 | 2022 |
| Incorporating expert domain knowledge into causal structure discovery workflows J Mäkelä, L Melkas, I Mammarella, T Nieminen, S Chandramouli, ... Biogeosciences 19 (8), 2095-2099, 2022 | 3 | 2022 |
| Visual data exploration as a statistical testing procedure: Within-view and between-view multiple comparisons R Savvides, A Henelius, E Oikarinen, K Puolamäki IEEE Transactions on Visualization and Computer Graphics, 2022 | 2 | 2022 |
| Model selection with bootstrap validation R Savvides, J Mäkelä, K Puolamäki Statistical Analysis and Data Mining: The ASA Data Science Journal 16 (2 …, 2023 | 1 | 2023 |
| Applying machine learning to replicate large-eddy simulation results on urban pollutant dispersion M Kurppa, MJ Lange, HJ Suominen, E Oikarinen, R Savvides, L Järvi, ... Proceedings of The Center of Excellence in Atmospheric Science (CoE ATM …, 2019 | | 2019 |
