Browsing Publikasjoner fra Cristin by Title
Now showing items 139-158 of 285
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Learning latent representations of bank customers with the Variational Autoencoder
(Journal article; Peer reviewed, 2020)Learning data representations that reflect the customers’ creditworthiness can improve marketing campaigns, customer relationship management, data and process management or the credit risk assessment in retail banks. In ... -
Lenking og kobling i Historisk befolkningsregister
(Peer reviewed; Journal article, 2020)Historisk befolkningsregister, HBR, er et register over den norske befolkningen fra 1801 frem til Det sentrale folkeregisteret fra 1964. Det lages ved å lenke sammen personforekomster av samme person i folketellinger og ... -
A logic based event controller for means-end reasoning in simulation environments
(Journal article, 2023)Simulation games are designed to cultivate expertise and rehearse particular skill sets. In order to yield longitudinal effects, sequences of events must be crafted to yield intended learning outcomes, sometimes by focusing ... -
Lusebeitingsadferd hos rognkjeks
(Research report, 2020) -
Machine Learning + Marine Science: Critical Role of Partnerships in Norway
(Others, 2021)In this essay, we review some recent advances in developing machine learning (ML) methods for marine science applications in Norway. We focus mostly on deep learning (DL) methods and review the challenges we have faced in ... -
A mammography classification model trained from image labels only
(Journal article; Peer reviewed, 2022) -
MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data
(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 ... -
Mixing up contrastive learning: Self-supervised representation learning for time series
(Journal article; Peer reviewed, 2022) -
Mixing up contrastive learning: Self-supervised representation learning for time series
(Journal article; Peer reviewed, 2022) -
Mobile Sensing in Substance Use Research: A Scoping Review
(Peer reviewed; Journal article, 2020) -
Modeling dyslexic students' motivation for enhanced learning in E-learning systems
(Journal article; Peer reviewed, 2020)E-Learning systems can support real-time monitoring of learners’ learning desires and effects, thus offering opportunities for enhanced personalized learning. Recognition of the determinants of dyslexic users’ motivation ... -
Motvirkning av ensomhet gjennom inkludering i informasjonssamfunnet: iStøtet sluttrapport
(Report at the Norwegian Computing Center;, Research report, 2023)Eldre personer med nedsatt syn opplever mer ensomhet enn andre og er mindre digitale. Det å være en del av informasjonssamfunnet gjennom å ha tilgang til og å kunne bruke digitale verktøy har betydning for den enkeltes ... -
Motvirkning av ensomhet gjennom inkludering i informasjonssamfunnet: iStøtet sluttrapport
(NR-rapport;1061, Research report, 2023)Eldre personer med nedsatt syn opplever mer ensomhet enn andre og er mindre digitale. Det å være en del av informasjonssamfunnet gjennom å ha tilgang til og å kunne bruke digitale verktøy har betydning for den enkeltes ... -
Movement acts in breakdown situations: How a robot's recovery procedure affects participants' opinions
(Journal article; Peer reviewed, 2021)Recovery procedures are targeted at correcting issues encountered by robots. What are people’s opinions of a robot during these recovery procedures? During an experiment that examined how a mobile robot moved, the robot ... -
The Multi-Color Contrast Checker (M3C)
(Chapter, 2023)Accessible and readable contrast of text and graphical elements is a key requirement of the universal design of digital interfaces for people with and without disabilities. Many manual and automatic tools have been developed ... -
Multi-View Self-Constructing Graph Convolutional Networks With Adaptive Class Weighting Loss for Semantic Segmentation
(Chapter, 2020)We propose a novel architecture called the Multi-view Self-Constructing Graph Convolutional Networks (MSCG-Net) for semantic segmentation. Building on the recently proposed Self-Constructing Graph (SCG) module, which makes ... -
Named Entity Recognition without Labelled Data: A Weak Supervision Approach
(Chapter, 2020)Named Entity Recognition (NER) performance often degrades rapidly when applied to target domains that differ from the texts observed during training. When in-domain labelled data is available, transfer learning techniques ... -
A new framework for semi-Markovian parametric multi-state models with interval censoring
(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 ... -
A new framework for semi-Markovian parametric multi-state models with interval censoring
(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 ...