Browsing NR vitenarkiv by Title
Now showing items 83-102 of 288
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Efficient and simple prediction explanations with groupShapley: A practical perspective
(Peer reviewed; Journal article, 2021) -
Er jeg gammel nok til å bruke høreapparat? – Tolv personer med nedsatt hørsel forteller om sine erfaringer med teknologi
(Report at the Norwegian Computing Center;, Research report, 2022) -
Estimated effectiveness of treatments against salmon lice in marine salmonid farming
(Journal article; Peer reviewed, 2023)We here estimate the effectiveness of ten types of salmon lice treatments currently used in the salmonid industry by analysing daily and cage-wise data from 90 full production cycles from farms spread along the Norwegian ... -
Estimating the effect of biofouling on ship shaft power based on sensor measurements
(Journal article; Peer reviewed, 2022) -
Estimating Traffic in Urban Areas from Very-High Resolution Aerial Images
(Journal article; Peer reviewed, 2021)Traffic estimation from very-high-resolution remote-sensing imagery has received increasing interest during the last few years. In this article, we propose an automatic system for estimation of the annual average daily ... -
Estimation of Thickness and Layering of Johansen and Cook Sandstones at the Potential Co2 Storage Site Aurora
(Chapter, 2021)We have estimated the reservoir sand thickness and internal layering in the Aurora area, a planned geological CO2 storage site in the northern North Sea. The results are obtained by stochastic Markov chain Monte Carlo ... -
Et forslag til strømstøtte basert på timespriser
(Others, 2023)Jeg foreslår at strømstøtten blir timebasert, med en støtte på 90 prosent av spotpris over cirka 87 øre. Den hindrer både gratisstrøm, negative priser og ekstrempriser og gir samme kostnad for staten. -
Evaluation of CMIP5 and CMIP6 simulations of historical surface air temperature extremes using proper evaluation methods
(Journal article; Peer reviewed, 2020)Reliable projections of extremes by climate models are becoming increasingly important in the context of climate change and associated societal impacts. Extremes are by definition rare events, characterized by a small ... -
Evaluation of echosounder data preparation strategies for modern machine learning models
(Journal article; Peer reviewed, 2022) -
Evidence in the fog – Triage in fog computing systems
(Journal article; Peer reviewed, 2023)Fog computing promises improved service scalability and lower latency for IoT systems. The concept closes the gap between full computing capabilities at the network's edge and cloud systems' centrally located processing ... -
The evolution of a mobile payment solution network
(Journal article; Peer reviewed, 2019)Vipps is a peer-to-peer mobile payment solution launched by Norway’s largest financial services group DNB. The Vipps transaction data may be viewed as a graph with users corresponding to the nodes, and the financial ... -
Evolutionary Game for Confidentiality in IoT-Enabled Smart Grids
(Peer reviewed; Journal article, 2020) -
Explaining decisions of deep neural networks used for fish age prediction
(Peer reviewed; Journal article, 2020) -
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values
(Journal article; Peer reviewed, 2021)Explaining complex or seemingly simple machine learning models is an important practical problem. We want to explain individual predictions from such models by learning simple, interpretable explanations. Shapley value is ... -
Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees
(Chapter, 2022)It is becoming increasingly important to explain complex, black-box machine learning models. Although there is an expanding literature on this topic, Shapley values stand out as a sound method to explain predictions from ... -
eXplego: An interactive Tool that Helps you Select Appropriate XAI-methods for your Explainability Needs
(Journal article; Peer reviewed, 2023)The growing demand for transparency, interpretability, and explainability of machine learning models and AI systems has fueled the development of methods aimed at understanding the properties and behavior of such models ...