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    • Real-time prediction of propulsion motor overheating using machine learning 

      Hellton, Kristoffer Herland; Tveten, Martin; Stakkeland, Morten; Engebretsen, Solveig; Haug, Ola; Aldrin, Magne Tommy (Journal article; Peer reviewed, 2021)
    • Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective 

      Trosten, Daniel Johansen; Jenssen, Robert; Kampffmeyer, Michael (Journal article; Peer reviewed, 2021)
    • Rejoinder for the discussion of the paper "A Novel Algorithmic Approach to Bayesian Logic Regression" 

      Hubin, Aliaksandr; Storvik, Geir Olve; Frommlet, Florian (Peer reviewed; Journal article, 2020)
    • Rejoinder for the discussion of the paper "A Novel Algorithmic Approach to Bayesian Logic Regression" 

      Hubin, Aliaksandr; Storvik, Geir Olve; Frommlet, Florian (Peer reviewed; Journal article, 2020)
      Logic regression was developed more than a decade ago as a tool to construct predictors from Boolean combinations of binary covariates. It has been mainly used to model epistatic effects in genetic association studies, ...
    • Remote Evaluation in Universal Design Using Video Conferencing Systems During the COVID-19 Pandemic 

      Simon-Liedtke, Joschua Thomas; Bong, Way Kiat; Schulz, Trenton Wade; Fuglerud, Kristin Skeide (Chapter, 2021)
    • Report of the NAMMCO-ICES Workshop on Seal Modelling (WKSEALS 2020) 

      Smout, Sophie; Murray, Kimberly; Aarts, Geert; Biuw, Martin; Brasseur, Sophie; Buren, Alejandro; Empacher, Fanny; Frie, Anne Kirstine Højholt; Grecian, James; Hammill, Mike; Mikkelsen, Bjarni; Mosnier, Arnaud; Rosing-Asvid, Aqqalu; Russell, Debbie; Skaug, Hans Julius; Stenson, Garry; Thomas, Len; Ver Hoef, Jay; Witting, Lars; Zabavnikov, Vladimir; Øigård, Tor Arne; Fernandez, Ruth; Wickson, Fern (Journal article; Peer reviewed, 2021)
    • Reproducible Data Management and Analysis using R 

      Fjukstad, Bjørn; Shvetsov, Nikita; Nøst, Therese Haugdahl; Bøvelstad, Hege Marie; Halbach, Till; Holsbø, Einar; Hansen, Knut; Bongo, Lars Ailo (Chapter, 2020)
      Standardizing and documenting computational analyses is necessary to ensure reproducible results. We describe an R-based implementation of data management and preprocessing that is well integrated with the analysis tools ...
    • Risikomodell for vannskader på bygninger og sensitivitet i klimaframskrivninger 

      Heinrich, Claudio; Wahl, Jens Christian; Matre, Andreas; Thorarinsdottir, Thordis; Haug, Ola (;SAMBA/, Research report, 2020)
    • Risk-driven security metrics for an Android smartphone application 

      Savola, Reijo; Kylänpää, Markku; Abie, Habtamu (Journal article; Peer reviewed, 2020)
      Security management in Android smartphone platforms is a challenge. This challenge can be overcome at least partially by developing systematically risk-driven security objectives and controls for the target system, and ...
    • Robot-Enhanced Language Learning for Children in Norwegian Day-Care Centers 

      Halbach, Till; Schulz, Trenton; Leister, Wolfgang; Solheim, Ivar (Journal article; Peer reviewed, 2021)
    • Scalable change and anomaly detection in cross-correlated data 

      Tveten, Martin; Glad, Ingrid Kristine; Hjort, Nils Lid (Doctoral thesis, 2021)
    • Security in Android smartphone, Confidentiality in IoT-enabled Smart Grids, and Fault-tolerant privacy-preserving in AMS 

      Abie, Habtamu; Boudko, Svetlana; Eskeland, Sigurd (NR-notat;, Research report, 2020)
      The report summarizes the three journal papers which address security in android smartphone, confidentiality in IoT-enabled smart grids, and fault-tolerant privacy-preserving in AMS, respectively.
    • Security, Privacy, and Usability in Continuous Authentication: A Survey 

      Baig, Ahmed Fraz; Eskeland, Sigurd (Journal article; Peer reviewed, 2021)
    • Self-Constructing Graph Convolutional Networks for Semantic Labeling 

      Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt-Børre (Chapter, 2020)
      Graph Neural Networks (GNNs) have received increasing attention in many fields. However, due to the lack of prior graphs, their use for semantic labeling has been limited. Here, we propose a novel architecture called the ...
    • Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmentation of remote sensing images 

      Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre (Journal article; Peer reviewed, 2021)
      Capturing global contextual representations in remote sensing images by exploiting long-range pixel-pixel dependencies has been shown to improve segmentation performance. However, how to do this efficiently is an open ...
    • Semi-supervised target classification in multi-frequency echosounder data 

      Choi, Changkyu; Kampffmeyer, Michael; Handegard, Nils Olav; Salberg, Arnt Børre; Brautaset, Olav; Eikvil, Line; Jenssen, Robert (Journal article; Peer reviewed, 2021)
      Acoustic target classification in multi-frequency echosounder data is a major interest for the marine ecosystem and fishery management since it can potentially estimate the abundance or biomass of the species. A key problem ...
    • shapr: An R-package for explaining machine learning models with dependence-aware Shapley values 

      Sellereite, Nikolai; Jullum, Martin (Journal article; Peer reviewed, 2020)
    • Signals of Death - Post-Diagnostic Single Gene Expression Trajectories in Breast Cancer - A Proof of Concept 

      Lund, Eiliv; Holden, Marit; Thalabard, Jean-Christophe; Rasmussen Busund, Lill-Tove; Snapkov, Igor; Holden, Lars (Chapter, 2020)
      Using the time-dependent dynamics of gene expression from immune cells in blood, we aimed to explore single gene expression trajectories as biomarkers for death after a diagnosis of breast cancer introducing a new statistical ...
    • Situated Abilities within Universal Design – A Theoretical Exploration 

      Saplacan, Diana; Herstad, Jo; Schulz, Trenton Wade (Peer reviewed; Journal article, 2020)
      This paper investigates Universal Design (UD) through the idea of designing for situated abilities, rather than focusing on designing for disabled users. This shift in perspective from disabilities to abilities is explored ...
    • Situated Abilities within Universal Design – A Theoretical Exploration 

      Saplacan, Diana; Herstad, Jo; Schulz, Trenton Wade (Peer reviewed; Journal article, 2020)
      This paper investigates Universal Design (UD) through the idea of designing for situated abilities, rather than focusing on designing for disabled users. This shift in perspective from disabilities to abilities is explored ...

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