SAMBA
SAMBA
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
Hubin, Aliaksandr; Storvik, Geir Olve. Sparse Bayesian Neural Networks: Bridging Model and Parameter Uncertainty through Scalable Variational Inference. Mathematics (ISSN 2227-7390). 12(6) doi: 10.3390/math12060788. 2024.
Lutz, Julia; Roksvåg, Thea Julie Thømt; Dyrrdal, Anita Verpe; Lussana, Cristian; Thorarinsdottir, Thordis Linda. Areal reduction factors from gridded data products. Journal of Hydrology (ISSN 0022-1694). 635 pp 1-12. doi: 10.1016/j.jhydrol.2024.131177. 2024.
Fall, Johanna Jennifer Elisabeth; Gjøsæter, Harald; Tvete, Ingunn Fride; Aldrin, Magne Tommy. Classification of acoustic survey data: A comparison between seven teams of experts. Fisheries Research (ISSN 0165-7836). 274 doi: 10.1016/j.fishres.2024.107005. 2024.
Olsen, Lars Henry Berge; Glad, Ingrid Kristine; Jullum, Martin; Aas, Kjersti. A comparative study of methods for estimating model-agnostic Shapley value explanations. Data mining and knowledge discovery (ISSN 1384-5810). doi: 10.1007/s10618-024-01016-z. 2024. Institutional archive
Redelmeier, Annabelle Alice; Jullum, Martin; Aas, Kjersti; Løland, Anders. MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data. Data mining and knowledge discovery (ISSN 1384-5810). doi: 10.1007/s10618-024-01017-y. 2024.