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Institutt for fysikk og teknologi michael.c.kampffmeyer@uit.no +4777625264 Her finner du meg

Michael Christian Kampffmeyer

Førsteamanuensis / Gruppeleder Maskinlæring

Stillingsbeskrivelse

Member of the UiT Machine Learning Group. 

Personal website

 

  • 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, Robert Jenssen, Nils Olav Handegard, Arnt-Børre Salberg :
    Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data
    IEEE Journal of Oceanic Engineering 2023 ARKIV / DOI
  • Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric Xing :
    Federated Partially Supervised Learning With Limited Decentralized Medical Images
    IEEE Transactions on Medical Imaging 2023 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 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 2023
  • 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
  • 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
  • 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
  • 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
  • Xujie Zhang, Yu Sha, Michael Kampffmeyer, Zhenyu Xie, Zequn Jie, Chengwen Huang m.fl.:
    ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design
    SIGMM Records 2022
  • Kristoffer Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, Robert Jenssen :
    Mixing up contrastive learning: Self-supervised representation learning for time series
    Pattern Recognition Letters 2022 ARKIV / DOI
  • Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric Xing :
    Towards robust partially supervised multi-structure medical image segmentation on small-scale data
    Applied Soft Computing 2022 ARKIV / DOI
  • Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen :
    Generating customer's credit behavior with deep generative models
    Knowledge-Based Systems 2022 ARKIV / DOI
  • Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer :
    Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
    Medical Image Analysis 2022 ARKIV / DOI
  • Luigi Tommaso Luppino, Mads Adrian Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen m.fl.:
    Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
    IEEE Transactions on Neural Networks and Learning Systems 12. mai 2022 DOI
  • Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu :
    Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images
    Lecture Notes in Computer Science (LNCS) 2022 DOI
  • Srishti Gautam, Marina Marie-Claire Hohne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer :
    Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation
    IEEE International Symposium on Biomedical Imaging 2022 DOI
  • Zaiyu Huang, Hanhui Li, Zhenyu Xie, Michael Kampffmeyer, Qingling Cai, Xiaodan Liang :
    Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning
    Advances in Neural Information Processing Systems 2022 DOI
  • Xiao Dong, Xunlin Zhan, Yangxin Wu, Yunchao Wei, Michael Kampffmeyer, Xiaoyong Wei m.fl.:
    M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining
    Computer Vision and Pattern Recognition 2022 DOI
  • Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Eivindson Løkse, Gusatu Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer m.fl.:
    The Kernelized Taylor Diagram
    Communications in Computer and Information Science 2022 ARKIV / DOI
  • Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen :
    A self-guided anomaly detection-inspired few-shot segmentation network
    CEUR Workshop Proceedings 2022 ARKIV
  • Srishti Gautam, Marina Marie-Claire Hohne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer :
    This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation
    Pattern Recognition 2022 ARKIV / DOI
  • Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina Marie-Claire Hohne m.fl.:
    ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model
    Advances in Neural Information Processing Systems 2022 DOI
  • Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric Xing :
    Negational symmetry of quantum neural networks for binary pattern classification
    Pattern Recognition 2022 ARKIV / DOI
  • Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt Børre Salberg :
    Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks
    International Journal of Remote Sensing 2022 DOI
  • Ahcene Boubekki, Michael Kampffmeyer, Ulf Brefeld, Robert Jenssen :
    Joint optimization of an autoencoder for clustering and embedding.
    Machine Learning 2021 ARKIV / DOI
  • Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xiaodan Liang :
    Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN
    Advances in Neural Information Processing Systems 2021 ARKIV / DOI
  • Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Sebastiano Bruno Serpico, Robert Jenssen m.fl.:
    Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
    IEEE Transactions on Geoscience and Remote Sensing 2021 ARKIV / DOI
  • Fuwei Zhao, Zhenyu Xie, Michael Kampffmeyer, Haoye Dong, Songfang Han, Tianxiang Zheng m.fl.:
    M3D-VTON: A Monocular-to-3D Virtual Try-On Network
    IEEE International Conference on Computer Vision (ICCV) 2021 ARKIV / DOI
  • Daniel Johansen Trosten, Robert Jenssen, Michael Kampffmeyer :
    Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective
    Proceedings of the Northern Lights Deep Learning Workshop 2021 ARKIV / DOI
  • Ingeborg Mathiesen, Theodor Anton Ross, Anna Kaarina Pöntinen, Einar Holsbø, Michael Kampffmeyer, Mona Johannessen m.fl.:
    Characterization of Putative Virulence Factors in Enterococcus faecium
    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
  • Srishti Gautam, Marina Marie-Claire Hohne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer :
    Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation
    2022
  • Srishti Gautam, Marina Marie-Claire Hohne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer :
    Artifact Detection with Prototypical Relevance Propagation
    2022
  • Srishti Gautam, Marina Marie-Claire Hohne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer :
    Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation
    2022
  • Samuel Kuttner, Luigi Tommaso Luppino, Kristoffer Wickstrøm, Nils Thomas Doherty Midtbø, Seyed Esmaeil Dorraji, Ana Oteiza m.fl.:
    Deep learning derived input function in dynamic 18F-FDG PET imaging of mice
    2022
  • Kristoffer Wickstrøm, Eirik Agnalt Østmo, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen :
    Explaining representations for medical image retrieval
    2022
  • Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Eivindson Løkse, Gusatu Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer m.fl.:
    The Kernelized Taylor Diagram
    2022
  • Theodor Anton Ross, Anna Kaarina Pöntinen, Jessin Janice, Einar Holsbø, Jukka Corander, Kristin Hegstad m.fl.:
    Leveraging machine learning for finding novel putative virulence factors in Enterococcus faecium
    2022
  • Changkyu Choi, Shujian Yu, Michael Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Suaiba Amina Salahuddin m.fl.:
    Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior
    2022
  • Sigurd Eivindson Løkse, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen :
    Towards Explainable Representation Learning
    2021
  • Michael Kampffmeyer :
    Deep Clustering
    2021
  • Michael Kampffmeyer :
    UiT-gruppe får millionstøtte for å tolke bilder
    11. januar 2021
  • Michael Kampffmeyer :
    Fikk 12 millioner til bildetolking
    06. januar 2021
  • Michael Kampffmeyer, Robert Jenssen, Karl Øyvind Mikalsen, Sigurd Eivindson Løkse :
    Towards Explainable Representation Learning
    2021
  • Kristoffer Knutsen Wickstrøm, Sigurd Eivindson Løkse, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen :
    Towards Explainable Representation Learning
    2021
  • Kristoffer Knutsen Wickstrøm, Michael Kampffmeyer, Robert Jenssen :
    Advances in explainable DL & how to model uncertainty in explainability
    2021
  • Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer :
    Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision
    2021

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