Publikasjoner fra Cristin
Recent Submissions
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Tilgjengelige informasjonskapsler
(NR-rapport;, Research report, 2025)Prosjektet «Tilgjengelige informasjonskapsler» undersøker universell utforming av cookie-bannere og brukernes oppfatning av disse, med fokus på personer med funksjonsnedsettelser. Vi har gjennomført en litteraturstudie, ... -
DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning
(Peer reviewed; Journal article, 2024)The recent development of self-explainable deep learning approaches has focused on integrating well-defined explainability principles into learning process, with the goal of achieving these principles through optimization. ... -
Diffusion Models with Cross-Modal Data for Super-Resolution of Sentinel-2 To 2.5 Meter Resolution
(Peer reviewed; Journal article, 2024)Diffusion models have obtained photo-realistic results on various super-resolution tasks. However, existing approaches typically require the availability of high-resolution and paired training data, which often is not ... -
Rensefiskbetingelser: Betingelser som fremmer lusespising hos rensefisk Faglig sluttrapport for FHF-prosjekt Rensefiskbetingelser (P.nr.: 901766)
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Beyond output-mask comparison: A self-supervised inspired object scoring system for building change detection
(Journal article; Peer reviewed, 2024)Updating urban-area maps is crucial for urban planning and development. Traditional methods of updating urban-area maps based on aerial photography are labor-intensive and struggle to keep pace with rapid urban development. ... -
The aerosol pathway is crucial for observationally constraining climate sensitivity and anthropogenic forcing
(Journal article; Peer reviewed, 2024)Climate sensitivity and aerosol forcing are two of the most central, but uncertain, quantities in climate science that are crucial for assessing historical climate as well as future climate projections. Here, we use a ... -
Pilotprosjekt PO6: Scenariosimulering av lakselus i Midt-Norge
(NR-notat;, Research report, 2025)I dette notatet vurderer vi ulike tiltak mot lakselus i produksjonsområde 6 ved hjelp av scenariosimulering fra en lusemodell. Vi tilpasser lusemodellen til historiske data fra BarentsWatch. I modellen inngår smitte mellom ... -
A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction
(Journal article, 2023)Knowledge graphs are often used to represent structured information in a flexible and efficient manner, but their use in situated dialogue remains under-explored. This paper presents a novel conversational model for ... -
Incremental Dialogue Management: Survey, Discussion, and Implications for HRI
(Journal article, 2025)Efforts towards endowing robots with the ability to speak have benefited from recent advancements in NLP, in particular large language models. However, as powerful as current models have become, they still operate on ... -
Enhancing Naturalness in LLM-Generated Utterances through Disfluency Insertion
(Journal article, 2024)Disfluencies are a natural feature of spontaneous human speech but are typically absent from the outputs of Large Language Models (LLMs). This absence can diminish the perceived naturalness of synthesized speech, which is ... -
Areal reduction factors from gridded data products
(Journal article; Peer reviewed, 2024)Areal reduction factors (ARFs) convert a point estimate of extreme precipitation to an estimate of extreme precipitation over a spatial domain, and are commonly used in flood risk estimation. The fixed-area approach to ARF ... -
Predicting a food product’s missing nutritional values using machine learning and matching algorithms from natural language processing
(Research report, 2022)To analyze the nutritional trends of Norwegian households, Statistics Norway uses a combination of grocery store receipts and food product information, namely the nutritional values of each product. However, since the ... -
Efficient sparsity adaptive changepoint estimation
(Journal article; Peer reviewed, 2024)We propose a computationally efficient and sparsity adaptive procedure for estimating changes in unknown subsets of a high-dimensional data sequence. Assuming the data sequence is Gaussian, we prove that the new method ... -
Prediksjon av TVINN- varenummer ved bruk av maskinlæring på fritekstfelt
(NR-notat;, Research report, 2024)Statistisk sentralbyrå (SSB) publiserer månedlig statistikk over utenrikshandel med varer (UHV). Formålet med statistikken er å gi en oversikt over varestrømmene mellom Norge og utlandet. Eksport og import av varer er ... -
Insurance analytics: Prediction, explainability, and fairness
(Journal article; Peer reviewed, 2024)The expanding application of advanced analytics in insurance has generated numerous opportunities, such as more accurate predictive modeling powered by machine learning and artificial intelligence (AI) methods, the utilization ... -
Conversational Feedback in Scripted versus Spontaneous Dialogues: A Comparative Analysis
(Chapter, 2024)Scripted dialogues such as movie and TV subtitles constitute a widespread source of training data for conversational NLP models. However, there are notable linguistic differences between these dialogues and spontaneous ... -
Bayesian seismic 4D inversion for lithology and fluid prediction
(Peer reviewed; Journal article, 2024)Seismic data acquired at different times over the same area can provide insight into changes in an oil/gas reservoir. Probabilities for pore fluid will typically change, whereas the lithology remains stable over time. This ... -
National-Scale Detection of New Forest Roads in Sentinel-2 Time Series
(Peer reviewed; Journal article, 2024)The Norwegian Environment Agency is responsible for updating a map of undisturbed nature, which is performed every five years based on aerial photos. Some of the aerial photos are already up to five years old when a new ... -
Effect of testing criteria for infectious disease surveillance: The case of COVID-19 in Norway
(Peer reviewed; Journal article, 2024)During the COVID-19 pandemic in Norway, the testing criteria and capacity changed numerous times. In this study, we aim to assess consequences of changes in testing criteria for infectious disease surveillance. We plotted ... -
Fast spatial simulation of extreme high-resolution radar precipitation data using integrated nested Laplace approximations
(Peer reviewed; Journal article, 2024)Aiming to deliver improved precipitation simulations for hydrological impact assessment studies, we develop a methodology for modelling and simulating high-dimensional spatial precipitation extremes, focusing on both their ...
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