Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks. - Michael Kampffmeyer; Arnt-Børre Salberg; Robert Jenssen (CVPR Workshops, 2016)

Density ridge manifold traversal. - Jonas Nordhaug Myhre; Michael Kampffmeyer; Robert Jenssen (ICASSP, 2017)

Urban land cover classification with missing data using deep convolutional neural networks. - Michael Kampffmeyer; Arnt-Børre Salberg; Robert Jenssen (IGARSS, 2017)

Temporal overdrive recurrent neural network. - Filippo Maria Bianchi; Michael Kampffmeyer; Enrico Maiorino; Robert Jenssen (IJCNN, 2017)

Deep divergence-based clustering. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt-Børre Salberg; Robert Jenssen (MLSP, 2017)

Deep Kernelized Autoencoders. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi (SCIA (1), 2017)

Large-Scale Mapping of Small Roads in Lidar Images Using Deep Convolutional Neural Networks. - Arnt-Børre Salberg; Øivind Due Trier; Michael Kampffmeyer (SCIA (2), 2017)

An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting. - Filippo Maria Bianchi; Enrico Maiorino; Michael C. Kampffmeyer; Antonello Rizzi; Robert Jenssen (CoRR, 2017)

Recurrent Neural Networks for Short-Term Load Forecasting - An Overview and Comparative Analysis - Filippo Maria Bianchi; Enrico Maiorino; Michael C. Kampffmeyer; Antonello Rizzi; Robert Jenssen (Springer, 2017)

Towards deep anchor learning. - Mads A. Hansen; Karl Øyvind Mikalsen; Michael Kampffmeyer; Cristina Soguero-Ruíz; Robert Jenssen (BHI, 2018)

Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. - Andreas Storvik Strauman; Filippo Maria Bianchi; Karl Øyvind Mikalsen; Michael Kampffmeyer; Cristina Soguero-Ruíz; Robert Jenssen (BHI, 2018)

Query-Conditioned Three-Player Adversarial Network for Video Summarization. - Yujia Zhang 001; Michael Kampffmeyer; Xiaodan Liang; Min Tan 001; Eric P. Xing (BMVC, 2018)

Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Zeya Wang; Wei Dai 003; Eric P. Xing (MICCAI (2), 2018)

Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Zeya Wang; Wei Dai 003; Eric P. Xing (DLMIA/ML-CDS@MICCAI, 2018)

Uncertainty Modeling and interpretability in Convolutional Neural Networks for Polyp Segmentation. - Kristoffer Wickstrøm; Michael Kampffmeyer; Robert Jenssen (MLSP, 2018)

The deep kernelized autoencoder. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi (Appl. Soft Comput., 2018)

DTR-GAN: Dilated Temporal Relational Adversarial Network for Video Summarization. - Yujia Zhang 001; Michael Kampffmeyer; Xiaodan Liang; Dingwen Zhang; Min Tan 001; Eric P. Xing (CoRR, 2018)

Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders. - Filippo Maria Bianchi; Lorenzo Livi; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen (CoRR, 2018)

Segment-Based Credit Scoring Using Latent Clusters in the Variational Autoencoder. - Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen (CoRR, 2018)

Geometric Generalization Based Zero-Shot Learning Dataset Infinite World: Simple Yet Powerful. - Rajesh Chidambaram; Michael Kampffmeyer; Willie Neiswanger; Xiaodan Liang; Thomas Lachmann; Eric P. Xing (CoRR, 2018)

Urban Land Cover Classification With Missing Data Modalities Using Deep Convolutional Neural Networks. - Michael Kampffmeyer; Arnt-Børre Salberg; Robert Jenssen (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018)

DTR-GAN: dilated temporal relational adversarial network for video summarization. - Yujia Zhang 001; Michael Kampffmeyer; Xiaoguang Zhao; Min Tan 001 (ACM TUR-C, 2019)

Rethinking Knowledge Graph Propagation for Zero-Shot Learning. - Michael Kampffmeyer; Yinbo Chen; Xiaodan Liang; Hao Wang 014; Yujia Zhang 001; Eric P. Xing (CVPR, 2019)

Recurrent Deep Divergence-based Clustering for Simultaneous Feature Learning and Clustering of Variable Length Time Series. - Daniel J. Trosten; Andreas Storvik Strauman; Michael Kampffmeyer; Robert Jenssen (ICASSP, 2019)

Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network. - Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg (IGARSS, 2019)

Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images. - Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg (JURSE, 2019)

Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels. - Kristoffer Wickstrøm; Sigurd Løkse; Michael Kampffmeyer; Shujian Yu; José C. Príncipe; Robert Jenssen (CoRR, 2019)

Dilated temporal relational adversarial network for generic video summarization. - Yujia Zhang 001; Michael Kampffmeyer; Xiaodan Liang; Dingwen Zhang; Min Tan 001; Eric P. Xing (Multim. Tools Appl., 2019)

Deep divergence-based approach to clustering. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt-Børre Salberg; Robert Jenssen (Neural Networks, 2019)

Learning representations of multivariate time series with missing data. - Filippo Maria Bianchi; Lorenzo Livi; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen (Pattern Recognit., 2019)

ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. - Michael Kampffmeyer; Nanqing Dong; Xiaodan Liang; Yujia Zhang 001; Eric P. Xing (IEEE Trans. Image Process., 2019)

The 1st Agriculture-Vision Challenge: Methods and Results. - Mang Tik Chiu; Xingqian Xu; Kai Wang 058; Jennifer A. Hobbs; Naira Hovakimyan; Thomas S. Huang; Honghui Shi; Yunchao Wei; Zilong Huang; Alexander G. Schwing; Robert Brunner; Ivan Dozier; et al. (CVPR Workshops, 2020)

Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation. - Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg (CVPR Workshops, 2020)

SEN: A Novel Feature Normalization Dissimilarity Measure for Prototypical Few-Shot Learning Networks. - Van Nhan Nguyen; Sigurd Løkse; Kristoffer Wickstrøm; Michael Kampffmeyer; Davide Roverso; Robert Jenssen (ECCV (23), 2020)

Self-Constructing Graph Convolutional Networks for Semantic Labeling. - Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg (IGARSS, 2020)

Deep Image Clustering with Tensor Kernels and Unsupervised Companion Objectives. - Daniel J. Trosten; Michael C. Kampffmeyer; Robert Jenssen (CoRR, 2020)

SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation. - Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg (CoRR, 2020)

Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Min Xu 009; Irina Voiculescu; Eric P. Xing (CoRR, 2020)

Deep generative models for reject inference in credit scoring. - Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen (Knowl. Based Syst., 2020)

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps. - Kristoffer Wickstrøm; Michael Kampffmeyer; Robert Jenssen (Medical Image Anal., 2020)

Dense Dilated Convolutions' Merging Network for Land Cover Classification. - Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg (IEEE Trans. Geosci. Remote. Sens., 2020)

Quantum Unsupervised Domain Adaptation: Does Entanglement Help? - Nanqing Dong; Michael C. Kampffmeyer; Irina Voiculescu (BMVC, 2021)

Reconsidering Representation Alignment for Multi-View Clustering. - Daniel J. Trosten; Sigurd Løkse; Robert Jenssen; Michael Kampffmeyer (CVPR, 2021)

M3D-VTON: A Monocular-to-3D Virtual Try-On Network. - Fuwei Zhao; Zhenyu Xie; Michael Kampffmeyer; Haoye Dong; Songfang Han; Tianxiang Zheng; Tao Zhang; Xiaodan Liang (ICCV, 2021)

WAS-VTON: Warping Architecture Search for Virtual Try-on Network. - Zhenyu Xie; Xujie Zhang; Fuwei Zhao; Haoye Dong; Michael C. Kampffmeyer; Haonan Yan; Xiaodan Liang (ACM Multimedia, 2021)

Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN. - Zhenyu Xie; Zaiyu Huang; Fuwei Zhao; Haoye Dong; Michael Kampffmeyer; Xiaodan Liang (NeurIPS, 2021)

Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective. - Daniel J. Trosten; Robert Jenssen; Michael C. Kampffmeyer (NLDL, 2021)

Self-supervised Multi-task Representation Learning for Sequential Medical Images. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu (ECML/PKDD (3), 2021)

This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. - Srishti Gautam; Marina M.-C. Höhne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer (CoRR, 2021)

Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks. - Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg (CoRR, 2021)

RELAX: Representation Learning Explainability. - Kristoffer K. Wickstrøm; Daniel J. Trosten; Sigurd Løkse; Karl Øyvind Mikalsen; Michael C. Kampffmeyer; Robert Jenssen (CoRR, 2021)

Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI. - Stine Hansen; Samuel Kuttner; Michael Kampffmeyer; Tom-Vegard Markussen; Rune Sundset; Silje Kjærnes Øen; Live Eikenes; Robert Jenssen (Expert Syst. Appl., 2021)

Learning latent representations of bank customers with the Variational Autoencoder. - Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen (Expert Syst. Appl., 2021)

Joint optimization of an autoencoder for clustering and embedding. - Ahcène Boubekki; Michael Kampffmeyer; Ulf Brefeld; Robert Jenssen (Mach. Learn., 2021)

Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series. - Kristoffer Wickstrøm; Karl Øyvind Mikalsen; Michael Kampffmeyer; Arthur Revhaug; Robert Jenssen (IEEE J. Biomed. Health Informatics, 2021)

A self-guided anomaly detection-inspired few-shot segmentation network. - Suaiba Amina Salahuddin; Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen (CVCS, 2022)

M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining. - Xiao Dong; Xunlin Zhan; Yangxin Wu; Yunchao Wei; Michael C. Kampffmeyer; Xiaoyong Wei; Minlong Lu; Yaowei Wang 001; Xiaodan Liang (CVPR, 2022)

Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation. - Srishti Gautam; Marina M.-C. Höhne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer (ISBI, 2022)

Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu (MICCAI (8), 2022)

ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design. - Xujie Zhang; Yu Sha; Michael C. Kampffmeyer; Zhenyu Xie; Zequn Jie; Chengwen Huang; Jianqing Peng; Xiaodan Liang (ACM Multimedia, 2022)

The Kernelized Taylor Diagram. - Kristoffer Wickstrøm; Juan Emmanuel Johnson; Sigurd Løkse; Gustau Camps-Valls; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen (NAIS, 2022)

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. - Srishti Gautam; Ahcène Boubekki; Stine Hansen; Suaiba Amina Salahuddin; Robert Jenssen; Marina M.-C. Höhne; Michael Kampffmeyer (NeurIPS, 2022)

Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning. - Zaiyu Huang; Hanhui Li; Zhenyu Xie; Michael Kampffmeyer; Qingling Cai; Xiaodan Liang (NeurIPS, 2022)

Towards robust partially supervised multi-structure medical image segmentation on small-scale data. - Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Min Xu 009; Irina Voiculescu; Eric P. Xing (Appl. Soft Comput., 2022)

Automatic Identification of Chemical Moieties. - Jonas Lederer; Michael Gastegger; Kristof T. Schütt; Michael Kampffmeyer; Klaus-Robert Müller; Oliver T. Unke (CoRR, 2022)

PASTA-GAN++: A Versatile Framework for High-Resolution Unpaired Virtual Try-on. - Zhenyu Xie; Zaiyu Huang; Fuwei Zhao; Haoye Dong; Michael Kampffmeyer; Xin Dong; Feida Zhu 005; Xiaodan Liang (CoRR, 2022)

Generating customer's credit behavior with deep generative models. - Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen (Knowl. Based Syst., 2022)

Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels. - Stine Hansen; Srishti Gautam; Robert Jenssen; Michael Kampffmeyer (Medical Image Anal., 2022)

Negational symmetry of quantum neural networks for binary pattern classification. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Eric P. Xing (Pattern Recognit., 2022)

Mixing up contrastive learning: Self-supervised representation learning for time series. - Kristoffer Wickstrøm; Michael Kampffmeyer; Karl Øyvind Mikalsen; Robert Jenssen (Pattern Recognit. Lett., 2022)

Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection. - Luigi Tommaso Luppino; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; Sebastiano Bruno Serpico; Robert Jenssen; Stian Normann Anfinsen (IEEE Trans. Geosci. Remote. Sens., 2022)

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-Shot Learning with Hyperspherical Embeddings. - Daniel J. Trosten; Rwiddhi Chakraborty; Sigurd Løkse; Kristoffer Knutsen Wickstrøm; Robert Jenssen; Michael C. Kampffmeyer (CVPR, 2023)

On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering. - Daniel J. Trosten; Sigurd Løkse; Robert Jenssen; Michael C. Kampffmeyer (CVPR, 2023)

Supercm: Revisiting Clustering for Semi-Supervised Learning. - Durgesh Singh 003; Ahcène Boubekki; Robert Jenssen; Michael C. Kampffmeyer (ICASSP, 2023)

Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos. - Haoyuan Li; Haoye Dong; Hanchao Jia; Dong Huang; Michael C. Kampffmeyer; Liang Lin; Xiaodan Liang (ICCV, 2023)

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment. - Xujie Zhang; Binbin Yang; Michael C. Kampffmeyer; Wenqing Zhang; Shiyue Zhang; Guansong Lu; Liang Lin; Hang Xu 004; Xiaodan Liang (ICCV, 2023)

Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation. - Luca Tomasetti; Stine Hansen; Mahdieh Khanmohammadi; Kjersti Engan; Liv Jorunn Høllesli; Kathinka Dæhli Kurz; Michael Kampffmeyer (ISBI, 2023)

View it Like a Radiologist: Shifted Windows for Deep Learning Augmentation Of CT Images. - Eirik Agnalt Østmo; Kristoffer K. Wickstrøm; Keyur Radiya; Michael C. Kampffmeyer; Robert Jenssen (MLSP, 2023)

A clinically motivated self-supervised approach for content-based image retrieval of CT liver images. - Kristoffer Knutsen Wickstrøm; Eirik Agnalt Østmo; Keyur Radiya; Karl Øyvind Mikalsen; Michael Christian Kampffmeyer; Robert Jenssen (Comput. Medical Imaging Graph., 2023)

Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation. - Sara Björk; Stian Normann Anfinsen; Michael Kampffmeyer; Erik Næsset; Terje Gobakken; Lennart Noordermeer (CoRR, 2023)

Defending Against Malicious Behaviors in Federated Learning with Blockchain. - Nanqing Dong; Zhipeng Wang 009; Jiahao Sun; Michael Kampffmeyer; Yizhe Wen; Shuoying Zhang; William J. Knottenbelt; Eric P. Xing (CoRR, 2023)

WarpDiffusion: Efficient Diffusion Model for High-Fidelity Virtual Try-on. - Xujie Zhang; Xiu Li; Michael Kampffmeyer; Xin Dong; Zhenyu Xie; Feida Zhu 005; Haoye Dong; Xiaodan Liang (CoRR, 2023)

Data-Centric Machine Learning for Geospatial Remote Sensing Data. - Ribana Roscher; Marc Rußwurm; Caroline Gevaert; Michael Kampffmeyer; Jefersson A. dos Santos; Maria Vakalopoulou; Ronny Hänsch; Stine Hansen; Keiller Nogueira; Jonathan Prexl; Devis Tuia (CoRR, 2023)

Federated Partially Supervised Learning With Limited Decentralized Medical Images. - Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Eric P. Xing (IEEE Trans. Medical Imaging, 2023)

This looks More Like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. - Srishti Gautam; Marina M.-C. Höhne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer (Pattern Recognit., 2023)

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. - Kristoffer K. Wickstrøm; Sigurd Løkse; Michael C. Kampffmeyer; Shujian Yu; José C. Príncipe; Robert Jenssen (Entropy, 2023)

RELAX: Representation Learning Explainability. - Kristoffer K. Wickstrøm; Daniel J. Trosten; Sigurd Løkse; Ahcène Boubekki; Karl Øyvind Mikalsen; Michael C. Kampffmeyer; Robert Jenssen (Int. J. Comput. Vis., 2023)

ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement. - Stine Hansen; Srishti Gautam; Suaiba Amina Salahuddin; Michael Kampffmeyer; Robert Jenssen (Medical Image Anal., 2023)

PTUS: Photo-Realistic Talking Upper-Body Synthesis via 3D-Aware Motion Decomposition Warping. - Luoyang Lin; Zutao Jiang; Xiaodan Liang; Liqian Ma; Michael C. Kampffmeyer; Xiaochun Cao (AAAI, 2024)

ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations. - Rwiddhi Chakraborty; Adrian Sletten; Michael C. Kampffmeyer (CVPR, 2024)

ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation. - Hyeongji Kim; Changkyu Choi; Michael Kampffmeyer; Terje Berge; Pekka Parviainen; Ketil Malde (ECCV Workshops (17), 2024)

DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning. - Changkyu Choi; Shujian Yu; Michael Kampffmeyer; Arnt-Børre Salberg; Nils Olav Handegard; Robert Jenssen (ICASSP, 2024)

Diffusion Models with Cross-Modal Data for Super-Resolution of Sentinel-2 To 2.5 Meter Resolution. - Muhammad Sarmad; Michael C. Kampffmeyer; Arnt-Børre Salberg (IGARSS, 2024)

PSAIR: A Neuro-Symbolic Approach to Zero-Shot Visual Grounding. - Yi Pan; Yujia Zhang 001; Michael Kampffmeyer; Xiaoguang Zhao (IJCNN, 2024)

An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images. - Nanqing Dong; Michael Kampffmeyer; Haoyang Su; Eric P. Xing (Appl. Soft Comput., 2024)

MMTryon: Multi-Modal Multi-Reference Control for High-Quality Fashion Generation. - Xujie Zhang; Ente Lin; Xiu Li; Yuxuan Luo; Michael Kampffmeyer; Xin Dong; Xiaodan Liang (CoRR, 2024)

LSNetv2: Improving weakly supervised power line detection with bipartite matching. - Duy Khoi Tran; Van Nhan Nguyen; Davide Roverso; Robert Jenssen; Michael Kampffmeyer (Expert Syst. Appl., 2024)

Leveraging tensor kernels to reduce objective function mismatch in deep clustering. - Daniel J. Trosten; Sigurd Løkse; Robert Jenssen; Michael Kampffmeyer (Pattern Recognit., 2024)

Prototypical Self-Explainable Models Without Re-training. - Srishti Gautam; Ahcene Boubekki; Marina M.-C. Höhne; Michael Kampffmeyer (Trans. Mach. Learn. Res., 2024)

Discriminative multimodal learning via conditional priors in generative models. - Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen (Neural Networks, 2024)

Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images. - Luigi Tommaso Luppino; Mads A. Hansen; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; Robert Jenssen; Stian Normann Anfinsen (IEEE Trans. Neural Networks Learn. Syst., 2024)

Defending Against Poisoning Attacks in Federated Learning With Blockchain. - Nanqing Dong; Zhipeng Wang 009; Jiahao Sun; Michael Kampffmeyer; William J. Knottenbelt; Eric P. Xing (IEEE Trans. Artif. Intell., 2024)

REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability. - Kristoffer K. Wickstrøm; Thea Brüsch; Michael C. Kampffmeyer; Robert Jenssen (AAAI, 2025)

Robust Classification by Coupling Data Mollification with Label Smoothing. - Markus Heinonen; Ba-Hien Tran; Michael Kampffmeyer; Maurizio Filippone (AISTATS, 2025)

AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering. - Jing Wang 116; Songhe Feng; Kristoffer Knutsen Wickstrøm; Michael C. Kampffmeyer (CVPR, 2025)

A Hubness Perspective on Representation Learning for Graph-Based Multi-View Clustering. - Zheming Xu; He Liu; Congyan Lang; Tao Wang 011; Yidong Li; Michael C. Kampffmeyer (CVPR, 2025)

RefCap: Zero-shot Video Corpus Moment Retrieval Based on Refined Dense Video Captioning. - Yi Pan; Yujia Zhang 001; Michael Kampffmeyer; Xiaoguang Zhao (ICASSP, 2025)

Sitcom-Crafter: A Plot-Driven Human Motion Generation System in 3D Scenes. - Jianqi Chen; Panwen Hu; Xiaojun Chang; Zhenwei Shi; Michael Kampffmeyer; Xiaodan Liang (ICLR, 2025)

UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting. - Haoyuan Li; Yanpeng Zhou; Tao Tang; Jifei Song; Yihan Zeng; Michael Kampffmeyer; Hang Xu 004; Xiaodan Liang (ICLR, 2025)

Modelling Uncertainty in Graph Convolutional Networks for Edge Detection in Mammograms. - Fredrik A. Dahl; Amund Vedal; Line Eikvil; Solveig Thrun; Michael Kampffmeyer; Solveig Hofvind (MIUA (2), 2025)

Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance. - Suaiba Amina Salahuddin; Elisabeth Wetzer; Kristoffer Wickstrøm; Solveig Thrun; Michael Kampffmeyer; Robert Jenssen (SCIA (2), 2025)

Prompt-guided bidirectional deep fusion network for referring image segmentation. - Junxian Wu 001; Yujia Zhang 001; Michael Kampffmeyer; Xiaoguang Zhao (Neurocomputing, 2025)

UNAGI: Unified neighbor-aware graph neural network for multi-view clustering. - Zheming Xu; Congyan Lang; Lili Wei; Liqian Liang; Tao Wang 011; Yidong Li; Michael C. Kampffmeyer (Neural Networks, 2025)

HierGAT: hierarchical spatial-temporal network with graph and transformer for video HOI detection. - Junxian Wu 001; Yujia Zhang 001; Michael Kampffmeyer; Yi Pan; Chenyu Zhang; Shiying Sun; Hui Chang; Xiaoguang Zhao (Multim. Syst., 2025)

Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders. - Rogelio Andrade Mancisidor; Robert Jenssen; Shujian Yu; Michael Kampffmeyer (CoRR, 2025)

Optimizing Data Augmentation through Bayesian Model Selection. - Madi Matymov; Ba-Hien Tran; Michael Kampffmeyer; Markus Heinonen; Maurizio Filippone (CoRR, 2025)

DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion Models. - Muhammad Sarmad; Arnt-Børre Salberg; Michael Kampffmeyer (CoRR, 2025)

VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction. - Zijun Sun; Solveig Thrun; Michael Kampffmeyer (CoRR, 2025)

Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction. - Solveig Thrun; Stine Hansen; Zijun Sun; Nele Blum; Suaiba Amina Salahuddin; Kristoffer Wickstrøm; Elisabeth Wetzer; Robert Jenssen; Maik Stille; Michael Kampffmeyer (CoRR, 2025)

EnLVAM: Enhanced Left Ventricle Linear Measurements Utilizing Anatomical Motion Mode. - Durgesh Singh 003; Ahcene Boubekki; Qing Cao; Svein Arne Aase; Robert Jenssen; Michael Kampffmeyer (CoRR, 2025)

Tied Prototype Model for Few-Shot Medical Image Segmentation. - Hyeongji Kim; Stine Hansen; Michael Kampffmeyer (CoRR, 2025)

A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F]FDG PET imaging. - Christian Salomonsen; Luigi Tommaso Luppino; Fredrik Aspheim; Kristoffer Wickstrøm; Elisabeth Wetzer; Michael Kampffmeyer; Rodrigo Berzaghi; Rune Sundset; Robert Jenssen; Samuel Kuttner (CoRR, 2025)

SuperCM: Improving Semi-Supervised Learning and Domain Adaptation through differentiable clustering. - Durgesh Singh 003; Ahcène Boubekki; Robert Jenssen; Michael Kampffmeyer (CoRR, 2025)

WiseLVAM: A Novel Framework For Left Ventricle Automatic Measurements. - Durgesh Kumar Singh; Qing Cao; Sarina Thomas; Ahcène Boubekki; Robert Jenssen; Michael Kampffmeyer (CoRR, 2025)

SuperCM: Improving semi-supervised learning and domain adaptation through differentiable clustering. - Durgesh Kumar Singh; Ahcène Boubekki; Robert Jenssen; Michael Kampffmeyer (Pattern Recognit., 2026)