Michael Kampffmeyer
Ribana Roscher,
Marc Russwurm,
Caroline Gevaert,
Michael Christian Kampffmeyer,
Jefersson A. Dos Santos,
Maria Vakalopoulou
m.fl.:
Better, Not Just More: Data-centric machine learning for Earth observation
IEEE Geoscience and Remote Sensing Magazine 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
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Christian Kampffmeyer
:
Leveraging tensor kernels to reduce objective function mismatch in deep clustering
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
Muhammad Sarmad,
Michael Christian Kampffmeyer,
Arnt-Børre Salberg
:
Diffusion Models with Cross-Modal Data for Super-Resolution of Sentinel-2 To 2.5 Meter Resolution
IEEE International Geoscience and Remote Sensing Symposium proceedings 2024 DOI
Srishti Gautam,
Ahcene Boubekki,
Marina Marie-Claire Höhne,
Michael Christian Kampffmeyer
:
Prototypical Self-Explainable Models Without Re-training
Transactions on Machine Learning Research (TMLR) 2024 ARKIV
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
Luoyang Lin,
Zutao Jiang,
Xiaodan Liang,
Liqian Ma,
Michael Christian Kampffmeyer,
Xiaochun Cao
:
PTUS: Photo-Realistic Talking Upper-Body Synthesis via 3D-Aware Motion Decomposition Warping
Proceedings of the AAAI Conference on Artificial Intelligence 2024 DOI
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
Nanqing Dong,
Zhipeng Wang,
Jiahao Sun,
Michael Christian Kampffmeyer,
William Knottenbelt,
Eric Xing
:
Defending Against Poisoning Attacks in Federated Learning with Blockchain
Rwiddhi Chakraborty,
Adrian Sletten,
Michael Christian Kampffmeyer
:
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations
Computer Vision and Pattern Recognition 2024 DOI
Hyeongji Kim,
Changkyu Choi,
Michael Christian Kampffmeyer,
Terje Berge,
Pekka Parviainen,
Ketil Malde
:
ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation
Lecture Notes in Computer Science (LNCS) 2024
Kristoffer Vinther Olesen,
Ahcene Boubekki,
Michael Christian Kampffmeyer,
Robert Jenssen,
Anders Nymark Christensen,
Sune Hørlück
m.fl.:
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
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
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,
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
Kristoffer Wickstrøm,
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Ahcene Boubekki,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
m.fl.:
RELAX: Representation Learning Explainability
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
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
Durgesh Kumar Singh,
Ahcene Boubekki,
Robert Jenssen,
Michael Kampffmeyer
:
Supercm: Revisiting Clustering for Semi-Supervised Learning
Jonas Lederer,
Michael Gastegger,
Kristof T. Schütt,
Michael Christian Kampffmeyer,
Klaus-Robert Müller,
Oliver T. Unke
:
Automatic identification of chemical moieties
Xujie Zhang,
Binbin Yang,
Michael Christian Kampffmeyer,
Wenqing Zhang,
Shiyue Zhang,
Guansong Lu
m.fl.:
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
m.fl.:
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation
Haoyuan Li,
Haoye Dong,
Hanchao Jia,
Dong Huang,
Michael Christian Kampffmeyer,
Liang Lin
m.fl.:
Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos
IEEE International Conference on Computer Vision (ICCV) 2023 ARKIV
Michael Christian Kampffmeyer,
Joar Hystad
:
Michael (33) vant prestisjetung pris
05. juni 2024
Petter Bjørklund,
Michael Christian Kampffmeyer,
Arnt-Børre Salberg,
Robert Jenssen
:
Full klaff for KI-konferansen i Tromsø
uit.no 2024
Michael Christian Kampffmeyer,
Adrian Sletten
:
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations
2024
Michael Christian Kampffmeyer
:
Towards Explainable Deep Learning Models
2024
Michael Christian Kampffmeyer
:
Representation learning for deep clustering and few-shot learning
2024
Michael Christian Kampffmeyer
:
Towards Self-explainable Deep Learning Models
2024
Theodor Johannes Line Forgaard,
Alba Ordonez,
Srishti Gautam,
Anders Ueland Waldeland,
Jarle Hamar Reksten,
Michael Christian Kampffmeyer
m.fl.:
Foundation Models for Earth Observation
2024
Robert Jenssen,
Michael Christian Kampffmeyer
:
Visual Intelligence Research and Innovation
2024
Michael Christian Kampffmeyer
:
Michael (33) vant prestisjetung pris
06. juni 2024
Robert Jenssen,
Michael Christian Kampffmeyer
:
Visual Intelligence Research and Innovations
2024
Hyeongji Kim,
Changkyu Choi,
Michael Christian Kampffmeyer,
Terje Berge,
Pekka Parviainen,
Ketil Malde
:
ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation
2024
Hyeongji Kim,
Changkyu Choi,
Michael Christian Kampffmeyer,
Terje Berge,
Pekka Parviainen,
Ketil Malde
:
ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation
2024
Arnt-Børre Salberg,
Michael Christian Kampffmeyer
:
Trends in deep learning
2023
Michael Christian Kampffmeyer
:
Introduction to Transfer Learning
2023
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
Changkyu Choi,
Michael Christian Kampffmeyer,
Nils Olav Handegard,
Arnt-Børre Salberg,
Robert Jenssen
:
Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
2023
Michael Christian Kampffmeyer
:
Learning from limited labelled data for medical image segmentation
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
Michael Christian Kampffmeyer
:
Hva er kunstig intelligens (KI)? Muligheter og utfordringer
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
:
Self-Explainable Deep Learning
2023
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Forskningsinteresser
Computer Vision, Explainable AI, Medical Image Analysis, Multi-modal learning
