Michael Kampffmeyer
Associate Professor / Machine Learning
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
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
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
Jonas Lederer,
Michael Gastegger,
Kristof T. Schütt,
Michael Christian Kampffmeyer,
Klaus-Robert Müller,
Oliver T. Unke
:
Automatic identification of chemical moieties
Haoyuan Li,
Haoye Dong,
Hanchao Jia,
Dong Huang,
Michael Christian Kampffmeyer,
Liang Lin
et al.:
Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos
IEEE International Conference on Computer Vision (ICCV) 2023 ARKIV
Xujie Zhang,
Binbin Yang,
Michael Christian Kampffmeyer,
Wenqing Zhang,
Shiyue Zhang,
Guansong Lu
et al.:
DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment
IEEE International Conference on Computer Vision (ICCV) 2023 ARKIV
Luca Tomasetti,
Stine Hansen,
Mahdieh Khanmohammadi,
Kjersti Engan,
Liv Jorunn Høllesli,
Kathinka Dæhli Kurz
et al.:
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation
Changkyu Choi,
Michael Kampffmeyer,
Nils Olav Handegard,
Arnt-Børre Salberg,
Robert Jenssen
:
Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu,
Eric Xing
:
Federated Partially Supervised Learning With Limited Decentralized Medical Images
Durgesh Kumar Singh,
Ahcene Boubekki,
Robert Jenssen,
Michael Kampffmeyer
:
Supercm: Revisiting Clustering for Semi-Supervised Learning
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Kampffmeyer
:
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering
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
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
Kristoffer Wickstrøm,
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Ahcene Boubekki,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
et al.:
RELAX: Representation Learning Explainability
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
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
Rogelio Andrade Mancisidor,
Michael Christian Kampffmeyer,
Kjersti Aas,
Robert Jenssen
:
Discriminative multimodal learning via conditional priors in generative models
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
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu,
Eric Xing
:
Negational symmetry of quantum neural networks for binary pattern classification
Stine Hansen,
Srishti Gautam,
Robert Jenssen,
Michael Kampffmeyer
:
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
Kristoffer Wickstrøm,
Juan Emmanuel Johnson,
Sigurd Eivindson Løkse,
Gusatu Camps-Valls,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
et al.:
The Kernelized Taylor Diagram
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu
:
Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images
Lecture Notes in Computer Science (LNCS) 2022 DOI
Xiao Dong,
Xunlin Zhan,
Yangxin Wu,
Yunchao Wei,
Michael Kampffmeyer,
Xiaoyong Wei
et al.:
M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining
Computer Vision and Pattern Recognition 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
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
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
Ingeborg Mathiesen,
Theodor Anton Ross,
Anna Kaarina Pöntinen,
Einar Holsbø,
Michael Kampffmeyer,
Mona Johannessen
et al.:
Characterization of Putative Virulence Factors in Enterococcus faecium
2023
Magnus Oterhals Størdal,
Benjamin Ricaud,
Michael Christian Kampffmeyer,
Geir Bertelsen,
Maja Gran Erke
:
Risk Prediction of Diabetic Retinopathy in the Tromsø Study
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
Michael Christian Kampffmeyer
:
Learning from limited labeled data for few-shot medical image segmentation (and beyond)
2023
Michael Christian Kampffmeyer
:
Deep Clustering
2023
Michael Christian Kampffmeyer
:
UiT Machine Learning Group
2023
Michael Christian Kampffmeyer
:
Deep Multi-view Clustering
2023
Michael Christian Kampffmeyer
:
AI’S FUTURE PATH, WHAT ARE THE OPPORTUNITIES?
2023
Michael Christian Kampffmeyer
:
Self-Explainable Deep Learning
2023
Michael Christian Kampffmeyer
:
Hva er kunstig intelligens (KI)? Muligheter og utfordringer
2023
Michael Christian Kampffmeyer
:
Learning from limited labelled data for medical image segmentation
2023
Magnus Oterhals Størdal,
Benjamin Ricaud,
Michael Christian Kampffmeyer,
Geir Bertelsen,
Maja Gran Erke
:
Risk Prediction of Diabetic Retinopathy in the Tromsø Study
2023
Arnt-Børre Salberg,
Michael Christian Kampffmeyer
:
Trends in deep learning
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
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
Changkyu Choi,
Shujian Yu,
Michael Kampffmeyer,
Arnt-Børre Salberg,
Nils Olav Handegard,
Suaiba Amina Salahuddin
et al.:
Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior
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
Kristoffer Wickstrøm,
Juan Emmanuel Johnson,
Sigurd Eivindson Løkse,
Gusatu Camps-Valls,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
et al.:
The Kernelized Taylor Diagram
2022
Theodor Anton Ross,
Anna Kaarina Pöntinen,
Jessin Janice,
Einar Holsbø,
Jukka Corander,
Kristin Hegstad
et al.:
Leveraging machine learning for finding novel putative virulence factors in Enterococcus faecium
2022
Kristoffer Wickstrøm,
Eirik Agnalt Østmo,
Karl Øyvind Mikalsen,
Michael Kampffmeyer,
Robert Jenssen
:
Explaining representations for medical image retrieval
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
The 50 latest publications is shown on this page. See all publications in Cristin here →