Statistical Analysis, Machine Learning and Image Analysis - SAMBA
The SAMBA department has comprehensive theoretical and practical knowledge in the fields of statistics, machine learning and image analysis. We are one of Europe's largest and most competent groups within applied statistics and statistical-matematical modelling. We cover a broad spectrum of methods and are a world leader in some of these areas. The appropriate choice of method for the various problems is thus one of our strengths. Many calculations involve uncertainty and the accurate calculation of this quantity is an important speciality.
Last 5 scientific articles
Aldrin, Magne Tommy; Jansen, Peder A; Stryhn, Henrik. A partly stage-structured model for the abundance of salmon lice in salmonid farms. Epidemics (ISSN 1755-4365). pp 1-14. doi: 10.1016/j.epidem.2018.08.001. 2018.
Tvete, Ingunn Fride; Bjørner, Trine; Skomedal, Tor. Mental Health and Disability Pension Onset Changes in Consumption of Antianxiety and Hypnotic Drugs. Health Services Research and Managerial Epidemiology (ISSN 2333-3928). 5 doi: 10.1177/2333392818792683. 2018.
Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert. Urban land cover classification with missing data modalities using deep convolutional neural networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (ISSN 1939-1404). 11(6) pp 1758-1768. doi: 10.1109/JSTARS.2018.2834961. 2018.
Lund, Eiliv; Nakamura, Aurelie; Snapkov, Igor; Thalabard, Jean-Christophe; Olsen, Karina Standahl; Holden, Lars; Holden, Marit. Each pregnancy linearly changes immune gene expression in the blood of healthy women compared with breast cancer patients. Clinical Epidemiology (ISSN 1179-1349). doi: 10.2147/CLEP.S163208. 2018.
Guttorp, Peter; Thorarinsdottir, Thordis Linda. How to save Bergen from the sea? Decisions under uncertainty. Significance (ISSN 1740-9705). 15(2) pp 14-18. doi: 10.1111/j.1740-9713.2018.01125.x. 2018.