Nanqing Dong,
Michael Christian Kampffmeyer,
Haoyang Su,
Eric Xing
:
An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images
Applied Soft Computing 2024
DOI
Nanqing Dong,
Zhipeng Wang,
Jiahao Sun,
Michael Christian Kampffmeyer,
William Knottenbelt,
Eric Xing
:
Defending Against Poisoning Attacks in Federated Learning with Blockchain
IEEE Transactions on Artificial Intelligence (TAI) 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
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
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Christian Kampffmeyer
:
Leveraging tensor kernels to reduce objective function mismatch in deep clustering
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
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
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,
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
Rogelio Andrade Mancisidor,
Michael Christian Kampffmeyer,
Kjersti Aas,
Robert Jenssen
:
Discriminative multimodal learning via conditional priors in generative models
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
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu,
Eric Xing
:
Federated Partially Supervised Learning With Limited Decentralized Medical Images
IEEE Transactions on Medical Imaging 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
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
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
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
IEEE International Symposium on Biomedical Imaging 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
Jonas Lederer,
Michael Gastegger,
Kristof T. Schütt,
Michael Christian Kampffmeyer,
Klaus-Robert Müller,
Oliver T. Unke
:
Automatic identification of chemical moieties
Physical Chemistry, Chemical Physics - PCCP 2023
ARKIV /
DOI
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu,
Eric Xing
:
Negational symmetry of quantum neural networks for binary pattern classification
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,
Ahcene Boubekki,
Stine Hansen,
Suaiba Amina Salahuddin,
Robert Jenssen,
Marina Marie-Claire Hohne
et al.:
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model
Advances in Neural Information Processing Systems 2022
ARKIV /
DOI
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
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
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
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
Xujie Zhang,
Yu Sha,
Michael Kampffmeyer,
Zhenyu Xie,
Zequn Jie,
Chengwen Huang
et al.:
ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design
SIGMM Records 2022
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
Michael Christian Kampffmeyer,
Adrian Sletten
:
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations
2024
Arnt-Børre Salberg,
Michael Christian Kampffmeyer
:
Trends in deep learning
2023
Michael Christian Kampffmeyer
:
Learning from limited labeled data for few-shot medical image segmentation (and beyond)
2023
Magnus Oterhals Størdal,
Benjamin Ricaud,
Michael Christian Kampffmeyer,
Geir Bertelsen,
Maja Gran Erke
:
Risk Prediction of Diabetic Retinopathy in the Tromsø Study
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
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
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
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
:
UiT Machine Learning Group
2023
Michael Christian Kampffmeyer
:
Deep Clustering
2023
Michael Christian Kampffmeyer
:
Hva er kunstig intelligens (KI)? Muligheter og utfordringer
2023
Michael Christian Kampffmeyer
:
Self-Explainable Deep Learning
2023
Michael Christian Kampffmeyer
:
Learning from limited labelled data for medical image segmentation
2023
Michael Christian Kampffmeyer
:
AI’S FUTURE PATH, WHAT ARE THE OPPORTUNITIES?
2023
Michael Christian Kampffmeyer
:
Deep Multi-view Clustering
2023
Magnus Oterhals Størdal,
Benjamin Ricaud,
Michael Christian Kampffmeyer,
Geir Bertelsen,
Maja Gran Erke
:
Risk Prediction of Diabetic Retinopathy in the Tromsø Study
2023
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
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
Srishti Gautam,
Marina Marie-Claire Hohne,
Stine Hansen,
Robert Jenssen,
Michael Kampffmeyer
:
Artifact Detection with Prototypical Relevance Propagation
2022