Michael Kampffmeyer
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) 2025
Junxian Wu,
Yujia Zhang,
Michael Kampffmeyer,
Xiaoguang Zhao
:
Prompt-guided bidirectional deep fusion network for referring image segmentation
Neurocomputing 2025 DOI
Ribana Roscher,
Marc Russwurm,
Caroline Gevaert,
Michael Christian Kampffmeyer,
Jefersson A. Dos Santos,
Maria Vakalopoulou
et al.:
Better, Not Just More: Data-centric machine learning for Earth observation
IEEE Geoscience and Remote Sensing Magazine 2024 DOI
Nanqing Dong,
Zhipeng Wang,
Jiahao Sun,
Michael Christian Kampffmeyer,
William Knottenbelt,
Eric Xing
:
Defending Against Poisoning Attacks in Federated Learning with Blockchain
Yi Pan,
Yujia Zhang,
Michael Christian Kampffmeyer,
Xiaoguang Zhao
:
PSAIR: A Neuro-Symbolic Approach to Zero-Shot Visual Grounding
Duy Khoi Tran,
van Nhan Nguyen,
Davide Roverso,
Robert Jenssen,
Michael Christian Kampffmeyer
:
LSNetv2: Improving weakly supervised power line detection with bipartite matching
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
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Christian Kampffmeyer
:
Leveraging tensor kernels to reduce objective function mismatch in deep clustering
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
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
Rwiddhi Chakraborty,
Adrian Sletten,
Michael Christian Kampffmeyer
:
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations
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
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
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
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
et al.:
RELAX: Representation Learning Explainability
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
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
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
Elisabeth Wetzer,
Suaiba Amina Salahuddin,
Robert Jenssen,
Michael Christian Kampffmeyer,
Torkil Stoltz
:
Verdens nordligste KI-konferanse
08. January 2025
Michael Christian Kampffmeyer,
Joar Hystad
:
Michael (33) vant prestisjetung pris
05. June 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
et al.:
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. June 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
Muhammad Sarmad,
Michael Kampffmeyer,
Arnt-Børre Salberg
:
Towards a Controllable Diffusion Model for Photo-Realistic Super-Resolution of Sentinel-2
2024
Muhammad Sarmad,
Michael Kampffmeyer,
Arnt-Børre Salberg
:
Diffusion Models with Cross-Modal Data for Super-Resolution of Sentinel-2 To 2.5 Meter Resolution
2024
Theodor Johannes Line Forgaard,
Alba Ordonez,
Srishti Gautam,
Anders U. Waldeland,
Jarle Hamar Reksten,
Michael Kampffmeyer
et al.:
EO Foundation Model. Foundation Models for Climate and Society. Deliverable D1.1 Milestone 1
2024
Petter Bjørklund,
Michael Christian Kampffmeyer,
Arnt-Børre Salberg,
Robert Jenssen
:
Full klaff for KI-konferansen i Tromsø
uit.no 2024 FULLTEKST
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
et al.:
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
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