Recent Submissions

  • Efficient non-interactive anonymous communication 

    Eskeland, Sigurd; Boudko, Svetlana (Journal article; Peer reviewed, 2024)
    Methods for untraceable and anonymous communication, such as anonymous routing networks and dining cryptographers networks, are in general very complex and suffer from high performance overhead of a minimum order of ...
  • IoT cybersecurity in 5G and beyond: a systematic literature review 

    Pirbhulal, Sandeep; Chockalingam, Sabarathinam; Shukla, Ankur; Abie, Habtamu (Journal article; Peer reviewed, 2024)
    The 5th generation (5G) and beyond use Internet of Things (IoT) to offer the feature of remote monitoring for different applications such as transportation, healthcare, and energy. There are several advantages of 5G and ...
  • Assessing the Quality of Human-Generated Summaries with Weakly Supervised Learning 

    Olsen, Joakim; Næss, Arild Brandrud; Lison, Pierre (Chapter, 2021)
    This paper explores how to automatically measure the quality of human-generated summaries, based on a Norwegian corpus of real estate condition reports and their corresponding summaries. The proposed approach proceeds in ...
  • Stream ciphers - Cryptography 

    Eskeland, Sigurd (NR-notat;, Research report, 2024)
    The purpose of this report is to highlight security principles in relation to efficient cryptographic algorithms and provide a brief introduction to a few such prominent algorithms. A need for efficient cryptographic ...
  • Leveraging tensor kernels to reduce objective function mismatch in deep clustering 

    Trosten, Daniel Johansen; Løkse, Sigurd Eivindson; Jenssen, Robert; Kampffmeyer, Michael Christian (Journal article; Peer reviewed, 2024)
    Objective Function Mismatch (OFM) occurs when the optimization of one objective has a negative impact on the optimization of another objective. In this work we study OFM in deep clustering, and find that the popular ...
  • Guttastemning in a Box - Fostering Emotional Connections Beyond the Screen 

    Iversen, Kasper; Kvilhaug Magnussen, Knut Ole; Cerutti, Paolo; Torrado Vidal, Juan Carlos (Journal article; Peer reviewed, 2024)
  • Method development for mapping kelp using drones and satellite images: Results from the KELPMAP-Vega project 

    Gundersen, Hege; Hancke, Kasper; Salberg, Arnt Børre; Poulsen, Robert Nøddebo; Buls, Toms; Liu, Izzie Yi; Ghareeb, Medyan; Christie, Hartvig C; Kile, Maia Røst; Bekkby, Trine; Arvidsson, Karoline Slettebø; Kvile, Kristina Øie (NIVA-rapport;, Research report, 2024)
    The KELPMAP study demonstrated that high-resolution multispectral data from drones and satellites, combined with AI-based image analysis, can efficiently map kelp forests and other coastal habitats. The field campaign, ...
  • Project Smells for Early Detection of Problems with Benefits Realization 

    Tanilkan, Sinan; Hannay, Jo Erskine (Journal article; Peer reviewed, 2024)
    Although substantial research has provided guidance on how to identify and manage the benefits of new software solutions, ensuring the realization of those benefits remains a challenge. Inspired by the notion of code smells ...
  • Exploring active ageing in a community-based living environment: an ethnographic study in the Western Norway context 

    Førsund, Elise; Torrado Vidal, Juan Carlos; Fæø, Stein Erik; Reithe, Haakon; Patrascu, Monica; Husebø, Bettina Elisabeth Franziska (Journal article; Peer reviewed, 2024)
    Background: Age-friendly environments intend to promote active ageing by facilitating social, mental, and physical participation. This could potentially delay the onset of chronic complex conditions, enabling people to ...
  • Using Pattern Counts to Quantify the Difference Between a Pair of Three-Dimensional Realizations 

    Lilleborge, Marie; Hauge, Ragnar; Fjellvoll, Bjørn; Abrahamsen, Petter (Journal article; Peer reviewed, 2024)
    When comparing different ways of modeling discrete three-dimensional realizations such as facies, it is useful to have a measure of difference (or similarity) in the geometry of these realizations.We propose a method for ...
  • A volume-conserving representation of cell faces in corner point grids 

    Røe, Per; Hauge, Ragnar (Journal article; Peer reviewed, 2015)
    Corner point grids is currently the standard grid representation for use in reservoir simulation. The cell faces in corner point grids are traditionally represented as bilinear surfaces where the edges between the corner ...
  • User Interaction Data in Apps: Comparing Policy Claims to Implementations 

    Tang, Feiyang; Østvold, Bjarte Mayanja (Journal article; Peer reviewed, 2024)
    As mobile app usage continues to rise, so does the generation of extensive user interaction data, which includes actions such as swiping, zooming, or the time spent on a screen. Apps often collect a large amount of this ...
  • Statistical Embedding: Beyond Principal Components 

    Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders (Journal article; Peer reviewed, 2023)
    There has been an intense recent activity in embedding of very high-dimensional and nonlinear data structures, much of it in the data science and machine learning literature. We survey this activity in four parts. In the ...
  • Some recent trends in embeddings of time series and dynamic networks 

    Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders (Journal article; Peer reviewed, 2023)
    We give a review of some recent developments in embeddings of time series and dynamic networks. We start out with traditional principal components and then look at extensions to dynamic factor models for time series. Unlike ...
  • A comparative study of methods for estimating model-agnostic Shapley value explanations 

    Olsen, Lars Henry Berge; Glad, Ingrid Kristine; Jullum, Martin; Aas, Kjersti (Journal article; Peer reviewed, 2024)
    Shapley values originated in cooperative game theory but are extensively used today as a model-agnostic explanation framework to explain predictions made by complex machine learning models in the industry and academia. ...
  • MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data 

    Redelmeier, Annabelle Alice; Jullum, Martin; Aas, Kjersti; Løland, Anders (Journal article; Peer reviewed, 2024)
    We introduce MCCE: Monte Carlo sampling of valid and realistic Counterfactual Explanations for tabular data, a novel counterfactual explanation method that generates on-manifold, actionable and valid counterfactuals by ...
  • A new framework for semi-Markovian parametric multi-state models with interval censoring 

    Aastveit, Marthe Elisabeth; Cunen, Celine Marie Løken; Hjort, Nils Lid (Journal article; Peer reviewed, 2023)
    There are few computational and methodological tools available for the analysis of general multi-state models with interval censoring. Here, we propose a general framework for parametric inference with interval censored ...
  • Se meg - hør meg 

    Torrado, Juan Carlos; Skeide Fuglerud, Kristin; Simon-Liedtke, Joschua Thomas; Haugan, Anne-Bjørg; Dale, Marianne; Wiborg, Berit Lilly; Andersen, Rita (Research report, 2024)
    Interesseorganisasjoner som jobber med tilrettelegging for personer med funksjonsnedsettelser, får mange tilbakemeldinger om negative opplevelser med reiselivet. Det er dessuten gjort lite forskning på dette temaet, og det ...
  • Cryptanalysis of a privacy-preserving authentication scheme based on private set intersection 

    Eskeland, Sigurd (Journal article; Peer reviewed, 2024)
  • Data assimilation and statistical post-processing for numerical air quality predictions 

    Steinbakk, Gunnhildur Högnadóttir; Thorarinsdottir, Thordis Linda; Lahoz, William A.; Walker, Sam-Erik (NR-notat;, Research report, 2014)
    This is a joint report based on work by NILU and NR on the use of data assimilation and statistical post-processing tools to improve the air quality prediction in the context of the Bedre Byluft programme. The objective ...

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