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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.

Research areas

Last 5 scientific articles

    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.

    Skeie, Ragnhild Bieltvedt; Berntsen, Terje Koren; Aldrin, Magne Tommy; Holden, Marit; Myhre, Gunnar. Climate sensitivity estimates - Sensitivity to radiative forcing time series and observational data. Earth System Dynamics (ISSN 2190-4979). 9(2) pp 879-894. doi: 10.5194/esd-9-879-2018. 2018.

    Binde, Caroline Ditlev; Tvete, Ingunn Fride; Gåsemyr, Jørund Inge; Natvig, Bent; Klemp, Marianne. A multiple treatment comparison meta-analysis of monoamine oxidase type B inhibitors for Parkinson's disease. British Journal of Clinical Pharmacology (ISSN 0306-5251). doi: 10.1111/bcp.13651. 2018.

    Aqrawi, Lara Adnan; Jensen, Janicke Liaaen; Øijordsbakken, Gunnvor; Ruus, Ann-Kristin; Nygård, Ståle; Holden, Marit; Jonsson, Roland; Galtung, Hilde; Skarstein, Kathrine. Signalling pathways identified in salivary glands from primary Sjögren's syndrome patients reveal enhanced adipose tissue development. Autoimmunity (ISSN 0891-6934). 51(3) pp 135-146. doi: 10.1080/08916934.2018.1446525. 2018.

    Kvamme, Håvard; Sellereite, Nikolai; Aas, Kjersti; Sjursen, Steffen A. Søreide. Predicting mortgage default using convolutional neural networks. Expert systems with applications (ISSN 0957-4174). 102 pp 207-217. doi: 10.1016/j.eswa.2018.02.029. 2018.

Publications in 2018, 2017, 2016, 2015, 2014, earlier years
Postal address:
Norsk Regnesentral/
Norwegian Computing Center
P.O. Box 114 Blindern
NO-0314 Oslo
Visit address:
Norsk Regnesentral
Gaustadalleen 23a
Kristen Nygaards hus
NO-0373 Oslo.
(+47) 22 85 25 00
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Postal address: Norsk Regnesentral/Norwegian Computing Center, P.O. Box 114 Blindern, NO-0314 Oslo, Norway
Visit address: Norsk Regnesentral, Gaustadalleen 23a, Kristen Nygaards hus, NO-0373 Oslo.
Phone: (+47) 22 85 25 00
AddressHow to get to NR