Bilde av Jenssen, Robert
Bilde av Jenssen, Robert
Professor / Machine Learning / Centre Leader Visual Intelligence Institutt for fysikk og teknologi robert.jenssen@uit.no +4777646493 41699612 Her finner du meg

Robert Jenssen


Stillingsbeskrivelse

Director, Visual Intelligence. Visual Intelligence is a Centre for Research-based Innovation (SFI) funded by the Research Council of Norway and a consortium of private and public partners. We are at the international forefront in deep learning research for complex image analysis. Please see

SFI Visual Intelligence

Twitter: @SFI_VI

Co-Director, Integreat. Integreat is a Centre of Excellence (SFF) funded by the Research Council of Norway and the university partners, the University of Oslo and UiT The Arctic University of Norway. We are at the international forefront in knowledge-based machine learning. Please see

SFF Integreat

Professor, UiT Machine Learning Group. Please see

UiT Machine Learning Group 

Adjunct Professor:

Pioneer Centre for AI, University of Copenhagen

Norwegian Computing Center

Selected recent publications:

Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks. ICML 2024. (coordinates coming)

MAP IT to visualize representations. ICLR 2024. https://openreview.net/pdf?id=OKf6JtXtoy

Cauchy-Schwarz divergence information bottleneck for regression. ICLR, 2024. https://openreview.net/pdf?id=7wY67ZDQTE

ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement. Medical Image Analysis, 2023. https://doi.org/10.1016/j.media.2023.102870

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-Shot Learning With Hyperspherical Embeddings. CVPR, 2023. https://openaccess.thecvf.com/content/CVPR2023/html/Trosten_Hubs_and_Hyperspheres_Reducing_Hubness_and_Improving_Transductive_Few-Shot_Learning_CVPR_2023_paper.html

On the Effects of Self-Supervision and Contrastive Alignment in Deep Multi-View Clustering. CVPR, 2023. https://openaccess.thecvf.com/content/CVPR2023/html/Trosten_On_the_Effects_of_Self-Supervision_and_Contrastive_Alignment_in_Deep_CVPR_2023_paper.html

RELAX: Representation Learning Explainability. International Journal of Computer Vision, 2023. https://doi.org/10.1007/s11263-023-01773-2

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. NeurIPS, 2022. https://openreview.net/forum?id=L8pZq2eRWvX

Principle of Relevant Information for Graph Sparsification. UAI, 2022. https://proceedings.mlr.press/v180/yu22c.html

Anomaly Detection-inspired Few-shot Medical Image Segmentation through Self-supervision with Supervoxels. Medical Image Analysis, 2022. https://doi.org/10.1016/j.media.2022.102385

Clinically Relevant Features for Predicting the Severity of Surgical Site Infections. IEEE Journal of Biomedical and Health Informatics, 2021. https://doi.org/10.1109/JBHI.2021.3121038

Measuring Dependence with Matrix-based Entropy Functional. AAAI, 2021. https://doi.org/10.1609/aaai.v35i12.17288

Reconsidering Representation Alignment for Multi-view Clustering. CVPR, 2021. https://openaccess.thecvf.com/content/CVPR2021/papers/Trosten_Reconsidering_Representation_Alignment_for_Multi-View_Clustering_CVPR_2021_paper.pdf

Joint Optimization of an Autoencoder for Clustering and Embedding. Machine Learning, 2021. https://doi.org/10.1007/s10994-021-06015-5

Uncertainty-aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series. IEEE Journal of Biomedical and Health Informatics, 2020. https://doi.org/10.1109/JBHI.2020.3042637

SEN: A Novel Feature Normalization Dissimilarity Measure for Prototypical Few-Shot Learning Networks. ECCV, 2020. https://link.springer.com/chapter/10.1007/978-3-030-58592-1_8

Google Scholar Profile

 



  • Robert Jenssen :
    MAP IT to Visualize Representations
    International Conference on Learning Representations 2024
  • Shujian Yu, Sigurd Eivindson Løkse, Robert Jenssen, Jose Principe :
    Cauchy-Schwarz Divergence Information Bottleneck for Regression
    International Conference on Learning Representations 2024 FULLTEKST
  • 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
    International Conference on Learning Representations 2024
  • Daniel Johansen Trosten, Sigurd Eivindson Løkse, Robert Jenssen, Michael Christian Kampffmeyer :
    Leveraging tensor kernels to reduce objective function mismatch in deep clustering
    Pattern Recognition 2024 ARKIV / DOI
  • Samuel Kuttner, Luigi Tommaso Luppino, Laurence Convert, Otman Sarrhini, Roger Lecomte, Michael Christian Kampffmeyer m.fl.:
    Deep learning derived input function in dynamic [18F]FDG PET imaging of mice
    Frontiers in Nuclear Medicine 2024 ARKIV / DOI
  • Harald Lykke Joakimsen, Iver Martinsen, Luigi Tommaso Luppino, Andrew McDonald, Scott Hosking, Robert Jenssen :
    Interrogating Sea Ice Predictability with Gradients
    IEEE Geoscience and Remote Sensing Letters 2024 DOI
  • Kaizhong Zheng, Shujian Yu, Baojuan Li, Robert Jenssen, Badong Chen :
    BrainIB: Interpretable Brain Network-Based Psychiatric Diagnosis With Graph Information Bottleneck
    IEEE Transactions on Neural Networks and Learning Systems 2024 DOI
  • Jørgen Aarmo Lund, Per Joel Burman Burman, Ashenafi Zebene Woldaregay, Robert Jenssen, Karl Øyvind Mikalsen :
    Instruction-guided deidentification with synthetic test cases for Norwegian clinical text
    Proceedings of Machine Learning Research (PMLR) 2024
  • Changkyu Choi, Shujian Yu, Michael Christian Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Robert Jenssen :
    DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning
    Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2024 DOI
  • Duy Khoi Tran, van Nhan Nguyen, Davide Roverso, Robert Jenssen, Michael Christian Kampffmeyer :
    LSNetv2: Improving weakly supervised power line detection with bipartite matching
    Expert Systems With Applications 2024 ARKIV / DOI
  • 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 ARKIV / DOI
  • Changkyu Choi, Michael Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg, Robert Jenssen :
    Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data
    IEEE Journal of Oceanic Engineering 2023 ARKIV / DOI
  • Daniel Johansen Trosten, Sigurd Eivindson Løkse, Robert Jenssen, Michael Kampffmeyer :
    On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering
    Computer Vision and Pattern Recognition 22. august 2023 ARKIV / DATA / DOI
  • 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
    Computer Vision and Pattern Recognition 2023 ARKIV / DOI
  • Durgesh Kumar Singh, Ahcene Boubekki, Robert Jenssen, Michael Kampffmeyer :
    Supercm: Revisiting Clustering for Semi-Supervised Learning
    Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2023 ARKIV / DOI
  • Robert Jenssen, August Hansen :
    Intervju om KI innen helsesektoren på NRK Radio
    14. august 2024
  • Robert Jenssen, Kristoffer Knutsen Wickstrøm, Petter Bjørklund :
    Slik kan kunstig intelligens hjelpe legene
    Forskning.no 2024
  • Robert Jenssen, Keyur Radiya, Torkild Jemterud :
    Den store serien om KI (4:10) - Vaktskifte: Dr. KI stempler inn
    06. april 2024
  • Petter Bjørklund, Michael Christian Kampffmeyer, Arnt-Børre Salberg, Robert Jenssen :
    Full klaff for KI-konferansen i Tromsø
    uit.no 2024
  • Petter Bjørklund, Elisabeth Wetzer, Robert Jenssen :
    UiT-forsker invitert til prestisje-konferanse for Nobelpris-vinnere
    uit.no 2024
  • Petter Bjørklund, Robert Jenssen, Klas Henning Pettersen :
    Til Tromsø for å diskutere kunstig intelligens
    uit.no 2024
  • Robert Jenssen, Rolf Ole Lindsetmo, Therese Hoseth Blomsø, Solveig Sand-Hanssen Hofvind, Even A. Røed, Mathias K. Hauglid m.fl.:
    Hvordan implementerer vi KI for bruk i helsesektoren på en trygg måte?
    2024
  • Robert Jenssen :
    NRK-intervju om Northern Lights Deep Learning Conference 2024
    05. januar 2024
  • Robert Jenssen, Luigi Tommaso Luppino, Rune Endresen Ytreberg, Mark Andrew Girolami, Iver Martinsen, Harald Lykke Joakimsen :
    Midt i skitværet spår de bedre og raskere værmelding
    10. januar 2024
  • Robert Jenssen :
    Til Tromsø for å diskutere kunstig intelligens
    07. januar 2024
  • 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
    2024
  • Robert Jenssen :
    UiT – Et nasjonalt tyngdepunkt innen KI
    2024
  • Robert Jenssen :
    KI i havnæringene?
    2024
  • Robert Jenssen :
    Towards eXplainable AI (XAI) with deep learning
    2024
  • Robert Jenssen :
    KI og pasientsikkerhet
    2024
  • Robert Jenssen :
    AI for acoustic fish target detection and beyond
    2024
  • Robert Jenssen :
    Exploiting data acquisition knowledge for cardiac ultrasound and content-based CT image retrieval
    2024
  • Robert Jenssen :
    Kunstig intelligens i transfusjonsmedisin
    2024
  • Robert Jenssen, Shujian Yu :
    Discrepancies to incorporate knowledge
    2024
  • Robert Jenssen, Michael Christian Kampffmeyer :
    Visual Intelligence Research and Innovation
    2024
  • Robert Jenssen :
    Medical Image Analysis for Cardiac Ultrasound and CT Image Retrieval
    2024
  • Robert Jenssen :
    Kunstig intelligens - Hva er det? Hvordan kan det (mis)brukes?
    2024
  • Robert Jenssen :
    XAI for representation learning
    2024
  • Petter Bjørklund, Robert Jenssen, Kristoffer Knutsen Wickstrøm :
    KI har superkrefter som kan hjelpe legene våre
    uit.no 2024
  • Robert Jenssen, Ole-Christoffer Granmo, Eldrid Borgan :
    Kan norsk oppfinnelse revolusjonere kunstig intelligens?
    31. januar 2024
  • Robert Jenssen, Rolf Ole Lindsetmo, Karl Øyvind Mikalsen, Oddny Johnsen :
    Markerer Tromsøs fortrinn på kunstig intelligens
    19. april 2024
  • Robert Jenssen :
    Kunstig intelligens - Finnes det en mer "bankers" karrierevei?
    2024
  • Robert Jenssen :
    Kunstig intelligens Hva er det? Hvordan kan det (mis)brukes?
    2024
  • Robert Jenssen :
    Effekter av KI i ulike deler av samfunnet: Hvordan kan forskere og politikere bidra til at KI gagner oss best mulig?
    2024
  • Robert Jenssen, Michael Christian Kampffmeyer :
    Visual Intelligence Research and Innovations
    2024
  • Robert Jenssen :
    Presentasjon av toppforskning innen KI ved UiT
    2024
  • Changkyu Choi, Michael Christian Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg, Robert Jenssen :
    Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
    2023
  • Robert Jenssen :
    Deltaker i podcasten KA i KI
    08. desember 2023
  • Fredrik Emil Aspheim, Luigi Tommaso Luppino, Michael Christian Kampffmeyer, Robert Jenssen, Rune Sundset, Akos Samuel Kuttner :
    Interpretable deep learning model for input function estimation in small-animal 18F-FDG PET imaging
    2023
  • Fredrik Emil Aspheim, Samuel Kuttner, Luigi Tommaso Luppino, Rune Sundset, Michael Christian Kampffmeyer, Robert Jenssen :
    Deep learning derived input-function in dynamic PET-imaging
    2023

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