Anna Emilie Jennow Wedenborg,
Kristoffer Wickstrøm,
Lars Kai Hansen,
Morten Mørup,
Teresa Dorszewski
:
Explaining Latent Representations of Neural Networks with Archetypal Analysis
Proceedings of Machine Learning Research (PMLR) 2026
ARKIV
Eirik Agnalt Østmo,
Keyur Radiya,
Kristoffer Wickstrøm,
Michael Kampffmeyer,
Karl Øyvind Mikalsen,
Robert Jenssen
:
Liver, vessel, and tumor segmentation from partially labeled CT and multi-label masked learning
Proceedings of Machine Learning Research (PMLR) 01. januar 2026
ARKIV
Dina Svendsen Solskinnsbakk,
Sigurd Almli Hanssen,
Harald Lykke Joakimsen,
Vilde Benoni Gjærum,
Elisabeth Wetzer,
Kristoffer Wickstrøm
:
Reducing Manual Workload in SAR-Based Oil Spill Detection Through Uncertainty-Aware Deep Learning
Proceedings of Machine Learning Research (PMLR) 01. januar 2026
DOI /
ARKIV
Christian Salomonsen,
Luigi T. Luppino,
Fredrik Emil Aspheim,
Kristoffer Wickstrøm,
Elisabeth Wetzer,
Michael Kampffmeyer
m.fl.:
A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F] FDG PET imaging
EJNMMI Research 09. mars 2026
DOI /
ARKIV
Beets-Tan, Regina,
Corbetta, Valentina,
Dijkstra, Floris Six,
Kervadec, Hoel,
Silva, Wilson,
Kristoffer Wickstrøm
:
In-hoc Concept Representations to Regularise Deep Learning in Medical Imaging
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops 2025
ARKIV
Bjørn Leth Møller,
Bulat Ibragimov,
Christian Igel,
Kristoffer Wickstrøm,
Matthias Keicher,
Mohammad Farid Azampour
m.fl.:
NEMt: Fast Targeted Explanations for Medical Image Models via Neural Explanation Masks
Proceedings of Machine Learning Research (PMLR) 2025
ARKIV
Thea Brüsch,
Kristoffer Wickstrøm,
Mikkel N. Schmidt,
Tommy Sonne Alstrøm,
Robert Jenssen
:
FreqRISE: Explaining time series using frequency masking
Proceedings of Machine Learning Research (PMLR) 2025
DOI /
ARKIV
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
Communications in Computer and Information Science (CCIS) 12. oktober 2025
DOI /
ARKIV
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
DOI /
ARKIV
Kristoffer Wickstrøm,
Marina Marie-Claire Höhne,
Hedström, Anna
:
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation | SpringerLink
Lecture Notes in Computer Science (LNCS) 2025
DOI /
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
:
Kunstig intelligens akkurat nå - og hva det kan bety for universitetsbiblioteker
Siyan Chen,
Kristoffer Wickstrøm,
Robert Jenssen
:
Evaluating AI-based Weather Forecasting Models for Local Wind Speed Prediction in Northern Norway
Elisabeth Wetzer,
Gregor Decristoforo,
Kristoffer Wickstrøm
:
Collaborative Coding and Reproducible Research: A Three-Year Course Retrospective
Christian Salomonsen,
Samuel Kuttner,
Michael Kampffmeyer,
Robert Jenssen,
Kristoffer Wickstrøm,
Jong Chul Ye
m.fl.:
Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
Christian Salomonsen,
Samuel Kuttner,
Michael Kampffmeyer,
Robert Jenssen,
Kristoffer Wickstrøm,
Jong Chul Ye
m.fl.:
Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
Medical imaging meets Eurips (MedEurIPS) 07. desember 2025
DOI /
ARKIV
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