Robert Jenssen




  • 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
  • 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 DOI
  • 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 DOI
  • Samuel Kuttner, Luigi Tommaso Luppino, Laurence Convert, Otman Sarrhini, Roger Lecomte, Michael Christian Kampffmeyer et al.:
    Deep learning derived input function in dynamic [18F]FDG PET imaging of mice
    Frontiers in Nuclear Medicine 2024 DOI
  • Stine Hansen, Srishti Gautam, Suaiba Amina Salahuddin, Michael Christian Kampffmeyer, Robert Jenssen :
    ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement
    Medical Image Analysis 2023 ARKIV / DOI
  • Ane Blazquez-Garcia, Kristoffer Knutsen Wickstrøm, Shujian Yu, Karl Øyvind Mikalsen, Ahcene Boubekki, Angel Conde et al.:
    Selective Imputation for Multivariate Time Series Datasets with Missing Values
    IEEE Transactions on Knowledge and Data Engineering 2023 ARKIV / DOI
  • 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
    Machine Learning for Signal Processing 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. Aug 2023 ARKIV / DATA / DOI
  • 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
    Entropy 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
  • Kristoffer Wickstrøm, Daniel Johansen Trosten, Sigurd Eivindson Løkse, Ahcene Boubekki, Karl Øyvind Mikalsen, Michael Kampffmeyer et al.:
    RELAX: Representation Learning Explainability
    International Journal of Computer Vision 2023 ARKIV / DOI
  • 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 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, 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
  • Rogelio Andrade Mancisidor, Michael Christian Kampffmeyer, Kjersti Aas, Robert Jenssen :
    Discriminative multimodal learning via conditional priors in generative models
    Neural Networks 2023 ARKIV / DOI
  • Kristoffer Vinther Olesen, Ahcene Boubekki, Michael Christian Kampffmeyer, Robert Jenssen, Anders Nymark Christensen, Sune Hørlück et al.:
    A Contextually Supported Abnormality Detector for Maritime Trajectories
    Journal of Marine Science and Engineering (JMSE) 2023 ARKIV / DOI
  • 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
  • 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
  • Robert Jenssen :
    XAI for representation learning
    2023
  • Robert Jenssen :
    On representation learning with information theoretic criteria and a new method for representation learning interpretability
    2023
  • Robert Jenssen :
    Information theoretic approaches: To clustering, graph neural networks and for investigating the dynamics of learning
    2023
  • Robert Jenssen :
    Self-supervised learning with XAI
    2023
  • Robert Jenssen :
    Information Theory Meets Deep Learning
    2023
  • Robert Jenssen :
    Deep learning in image analysis, graphs, and a new measure of statistical dependency between graphs
    2023
  • Robert Jenssen :
    XAI for representation learning
    2023
  • Robert Jenssen :
    Kunstig intelligens i helse
    2023
  • Robert Jenssen :
    Kunstig intelligens – Hva er det? Hvor kan det (mis)brukes
    2023
  • Robert Jenssen :
    NRK-intervju Arendalsuka
    16. Aug 2023
  • Robert Jenssen :
    Kunstig intelligens i fremtidens helsetjenester
    30. Sep 2023
  • Robert Jenssen :
    A major Norwegian hub for AI research in health
    2023
  • Robert Jenssen :
    Stortinget: Kunstig intelligens i helse
    2023
  • Robert Jenssen :
    En offensiv offentlig politikk for kunstig intelligens i helsetjenesten
    2023
  • Robert Jenssen :
    Deltaker i podcasten KA i KI
    08. Dec 2023
  • Harald Lykke Joakimsen, Iver Martinsen, Luigi Tommaso Luppino, Robert Jenssen :
    "Explainable" IceNet with backpropagated gradients
    2023
  • Changkyu Choi, Michael Christian Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg, Robert Jenssen :
    Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
    2023
  • Daniel Johansen Trosten, Sigurd Eivindson Løkse, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen :
    RELAX: Representation Learning Explainability
    2022
  • Kristoffer Knutsen Wickstrøm, Daniel Johansen Trosten, Sigurd Eivindson Løkse, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen :
    RELAX: Representation Learning Explainability
    2022
  • Daniel Johansen Trosten, Kristoffer Wickstrøm, Shujian Yu, Sigurd Eivindson Løkse, Robert Jenssen, Michael Kampffmeyer :
    Deep Clustering with the Cauchy-Schwarz Divergence
    2022
  • Robert Jenssen :
    Pasientnær kunstig intelligens
    2022
  • Robert Jenssen :
    Visual Intelligence and environmental monitoring
    2022
  • Robert Jenssen :
    Towards XAI and Visual Intelligence for health
    2022
  • Robert Jenssen :
    Visual Intelligence advances deep learning research towards innovations
    2022
  • Robert Jenssen :
    Women in AI panel debate
    2022
  • Robert Jenssen :
    Towards XAI and Visual Intelligence for health
    2022
  • Robert Jenssen :
    Learning from limited data
    2022
  • Robert Jenssen :
    Machine Learning Research, AI Technology and Ethical Considerations
    2022
  • Robert Jenssen :
    Visual Intelligence and graph neural networks
    2022
  • Robert Jenssen :
    Mot framtidas helsevesen med kunstig intelligens
    2022
  • Robert Jenssen :
    Kunstig intelligens-utdanninger for helse ved UiT
    2022
  • Robert Jenssen :
    Paneldebatt framtidas helsevesen med AI
    2022

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