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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

    Trier, Øivind Due; Cowley, David C.; Waldeland, Anders Ueland. Using deep neural networks on airborne laser scanning data: results from a case study of semi-automatic mapping of archaeological topography on Arran, Scotland. Archaeological Prospection (ISSN 1075-2196). 26(2) pp 165-175. doi: 10.1002/arp.1731. 2019.

    Jenssen, Robert; Kampffmeyer, Michael C.. Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps. Medical Image Analysis (ISSN 1361-8415). doi: 10.1016/j.media.2019.101619. 2019.

    Hubin, Aliaksandr; Storvik, Geir Olve; Grini, Paul Eivind; Butenko, Melinka Alonso. Bayesian binomial regression model with a latent Gaussian field for analysis of epigenetic data. In: Proceedings of Computer Data Analysis and Modeling: Stochastics and Data Science 2019. Belarusian State University Press. (ISBN 978-985-566-811-5). pp 167-171. doi: 123456789/233357. 2019.

    Hubin, Aliaksandr. An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models. In: ACM International Conference Proceeding Series (ICPS): AIIPCC '19: Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing. (ISBN 978-1-4503-7633-4). pp 1-9. doi: 10.1145/3371425.3371641. 2019.

    Basse-O'Connor, Andreas; Heinrich, Claudio Constantin; Podolskij, Mark. On limit theory for functionals of stationary increments Lévy driven moving averages. Electronic Journal of Probability (ISSN 1083-6489). 24(79) pp 1-42. doi: 10.1214/19-EJP336. 2019.

Publications in 2020, 2019, 2018, 2017, 2016, 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