Thea Brüsch,
Kristoffer Wickstrøm,
Mikkel N. Schmidt,
Robert Jenssen,
Tommy Sonne Alstrøm
:
FLEXtime: Filterbank Learning to Explain Time Series
Communications in Computer and Information Science (CCIS) 14. oktober 2025
DOI /
ARKIV
Teresa Dorszewski,
Lenka Tětková,
Robert Jenssen,
Lars Kai Hansen,
Kristoffer Knutsen Wickstrøm
:
From Colors to Classes: Emergence of Concepts in Vision Transformers
Jing Wang,
Songhe Feng,
Kristoffer Wickstrøm,
Michael Kampffmeyer
:
AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering
Computer Vision and Pattern Recognition 2025
DOI /
ARKIV
Duy Khoi Tran,
Van Nhan Nguyen,
Kristoffer Wickstrøm,
Michael Kampffmeyer
:
WOODWORK: A deep-learning based framework for woodpecker damage detection in powerline inspection
International Journal of Electrical Power & Energy Systems 01. oktober 2025
DOI /
ARKIV
Solveig Thrun,
Stine Hansen,
Zijun Sun,
Nele Blum,
Suaiba Amina Salahuddin,
Kristoffer Wickstrøm
m.fl.:
Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
Lecture Notes in Computer Science (LNCS) 20. september 2025
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ARKIV
Kristoffer Wickstrøm,
Hedström, Anna,
Marina Marie-Claire Höhne
:
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation | SpringerLink
Lecture Notes in Computer Science (LNCS) 2025
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ARKIV
Kristoffer Wickstrøm,
Thea Brüsch,
Michael Kampffmeyer,
Robert Jenssen
:
REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability
| Proceedings of the AAAI Conference on Artificial Intelligence
Proceedings of the AAAI Conference on Artificial Intelligence 11. april 2025
DOI /
ARKIV
Lars Uebbing,
Harald Lykke Joakimsen,
Luigi Tommaso Luppino,
Iver Martinsen,
Andrew McDonald,
Kristoffer Wickstrøm
m.fl.:
Investigating the Impact of Feature Reduction for Deep Learning-based Seasonal Sea Ice Forecasting
Proceedings of Machine Learning Research (PMLR) 2025
DOI /
ARKIV
Suaiba Amina Salahuddin,
Elisabeth Wetzer,
Kristoffer Wickstrøm,
Solveig Thrun,
Michael Kampffmeyer,
Robert Jenssen
:
Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance
Lecture Notes in Computer Science (LNCS) 16. juni 2025
DOI /
ARKIV
Bjørn Møller,
Christian Igel,
Kristoffer Knutsen Wickstrøm,
Jon Sporring,
Robert Jenssen,
Bulat Ibragimov
:
Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
Kristoffer Wickstrøm,
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Ahcene Boubekki,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
m.fl.:
RELAX: Representation Learning Explainability
International Journal of Computer Vision 2023
DOI /
ARKIV
Ane Blazquez-Garcia,
Kristoffer Knutsen Wickstrøm,
Shujian Yu,
Karl Øyvind Mikalsen,
Ahcene Boubekki,
Angel Conde
m.fl.:
Selective Imputation for Multivariate Time Series Datasets with Missing Values
IEEE Transactions on Knowledge and Data Engineering 2023
DOI /
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ARKIV
Eirik Agnalt Østmo,
Kristoffer Wickstrøm,
Keyur Radiya,
Michael Kampffmeyer,
Robert Jenssen
:
View it like a radiologist: Shifted windows for deep learning augmentation of CT images
Daniel Johansen Trosten,
Rwiddhi Chakraborty,
Sigurd Eivindson Løkse,
Kristoffer Wickstrøm,
Robert Jenssen,
Michael Kampffmeyer
:
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings
Kristoffer Wickstrøm,
Eirik Agnalt Østmo,
Keyur Radiya,
Karl Øyvind Mikalsen,
Michael Kampffmeyer,
Robert Jenssen
:
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
Computerized Medical Imaging and Graphics 2023
DOI /
ARKIV /
ARKIV
Kristoffer Knutsen Wickstrøm,
Marina Marie-Claire Höhne
:
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus
Transactions on Machine Learning Research (TMLR) 2023
ARKIV
Kristoffer Wickstrøm,
Sigurd Eivindson Løkse,
Michael Kampffmeyer,
Shujian Yu,
José C. Príncipe,
Robert Jenssen
:
Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy
Solveig Thrun,
Stine Hansen,
Zijun Sun,
Nele Blum,
Suaiba Amina Salahuddin,
Xin Wang
m.fl.:
Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction
Christian Salomonsen,
Kristoffer Wickstrøm,
Samuel Kuttner,
Elisabeth Wetzer
:
Physics-Informed Deep Learning for Improved Input Function Estimation in Motion-Blurred Dynamic [18F]FDG PET Images
Christian Salomonsen,
Kristoffer Wickstrøm,
Samuel Kuttner,
Elisabeth Wetzer
:
Physics-informed deep learning for improved input function estimation in motion-blurred dynamic [18F]FDG PET images
Johan Mylius-Kroken,
Kristoffer Wickstrøm,
Elisabeth Wetzer,
Ali Ramezani-Kebrya,
Robert Jenssen
:
Can a Convex Partition caused by a CPWL Neural Network be used for Density Estimation?
National conference on image processing and machine learnin 2025
ARKIV
Christian Salomonsen,
Kristoffer Wickstrøm,
Samuel Kuttner,
Elisabeth Wetzer
:
Physics-Informed Deep Learning for Improved Input Function Estimation in Motion-Blurred Dynamic [18F]FDG PET Images
Lars Uebbing,
Harald Lykke Joakimsen,
Kristoffer Wickstrøm,
Michael Kampffmeyer,
Sebastien Francois Lefevre,
Arnt Børre Salberg
m.fl.:
NOFE - Neural Operator Function Embedding
Lars Uebbing,
Harald Lykke Joakimsen,
Kristoffer Wickstrøm,
Michael Kampffmeyer,
Sebastien Francois Lefevre,
Arnt Børre Salberg
m.fl.:
NOFE Neural Operator Function Embedding
Solveig Thrun,
Stine Hansen,
Zijun Sun,
Nele Blum,
Suaiba Amina Salahuddin,
Kristoffer Wickstrøm
m.fl.:
Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
Simen Strømme,
Kristoffer Wickstrøm,
Kristoffer Søvik,
Geir Lippestad,
Johannes Bergh
:
Politiske partier har lansert KI-chatboter
Elisabeth Wetzer,
Youssef Wally,
Artem Galushko,
Elisavet Kozyri,
Kristoffer Wickstrøm
:
How to Tackle Bias and Protect Privacy in the Age of AI?
Christian Salomonsen,
Kristoffer Wickstrøm,
Elisabeth Wetzer,
Samuel Kuttner
:
Physics-Informed Machine Learning for dynamic PET modeling
Christian Salomonsen,
Kristoffer Wickstrøm,
Elisabeth Wetzer,
Samuel Kuttner
:
Physics-informed deep learning for predicting the arterial input function in dynamic PET imaging
Suaiba Amina Salahuddin,
Elisabeth Wetzer,
Kristoffer Wickstrøm,
Solveig Thrun,
Michael Kampffmeyer,
Robert Jenssen
:
Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance
Christian Salomonsen,
Kristoffer Wickstrøm,
Elisabeth Wetzer,
Samuel Kuttner
:
Physics-informed deep learning for improved input function estimation in motion-blurred dynamic [18F]FDG PET images
Petter Bjørklund,
Kristoffer Knutsen Wickstrøm,
Keyur Radiya
:
Finner leverkreft med kunstig intelligens
Robert Jenssen,
Kristoffer Knutsen Wickstrøm,
Petter Bjørklund
:
Slik kan kunstig intelligens hjelpe legene
Kristoffer Knutsen Wickstrøm
:
Kunstig intelligens fra beslutningstøtte til beslutningstaker – hvem er ansvarlig når ting går galt?
Kristoffer Knutsen Wickstrøm
:
Forskningsfronten på kunstig intelligens
Lars Uebbing,
Harald Lykke Joakimsen,
Luigi Tommaso Luppino,
Iver Martinsen,
Andrew McDonald,
Kristoffer Knutsen Wickstrøm
m.fl.:
Investigating the Impact of Feature Reduction for Deep Learning-based Seasonal Sea Ice Forecasting
Kristoffer Knutsen Wickstrøm
:
Muligheter og utfordringer for kunstig intelligens i næringslivet
Petter Bjørklund,
Robert Jenssen,
Kristoffer Knutsen Wickstrøm
:
KI har superkrefter som kan hjelpe legene våre
Christian Salomonsen,
Kristoffer Knutsen Wickstrøm,
Elisabeth Wetzer,
Samuel Kuttner
:
Kinetic modeling based compound loss for deep learning derived input function prediction in dynamic [18F]FDG PET images of mice
Christian Salomonsen,
Kristoffer Knutsen Wickstrøm,
Elisabeth Wetzer,
Samuel Kuttner
:
Kinetic modeling based compound loss for deep learning derived input function prediction in dynamic [18F]FDG PET images of mice
Christian Salomonsen,
Kristoffer Knutsen Wickstrøm,
Elisabeth Wetzer,
Samuel Kuttner
:
Kinetic modeling based compound loss for deep learning derived input function prediction in dynamic [18F]FDG PET images of mice
Kristoffer Knutsen Wickstrøm
:
Morrasendinga fra NRK i Troms - Forskere ved UiT Norges arktiske universitet utvikler kunstig intelligens til å finne leverkreft.
Kristoffer Knutsen Wickstrøm
:
Facebook skal merke KI-bilder: – Stor nyhet
Kristoffer Knutsen Wickstrøm
:
Kunstig Intelligens, utfordringer og muligheter for næringslivet
Robert Jenssen,
Kristoffer Knutsen Wickstrøm
:
Ja takk til «krysskulturelle» prosjekter drevet fram av teknologiutvikling
Robert Jenssen,
Kristoffer Knutsen Wickstrøm
:
Hvordan bør fotavtrykket av regjeringens satsing på kunstig intelligens se ut i Nord-Norge i 2030?
Kristoffer Wickstrøm
:
The aggregation method matters in faithfulness evaluation of XAI
Andreas Kvammen,
Kristoffer Wickstrøm,
Samuel Kociscak,
Jakub Vaverka,
Libor Nouzák,
Arnaud Zaslavsky
m.fl.:
Machine learning detection of dust impact signals
Kristoffer Knutsen Wickstrøm
:
XAI for time series analysis
Kristoffer Knutsen Wickstrøm
:
XAI for understanding of SSL representations