Robert Jenssen

Daniel Johansen Trosten; Sigurd Eivindson Løkse; Robert Jenssen; Michael Christian Kampffmeyer; Leveraging tensor kernels to reduce objective function mismatch in deep clustering Pattern Recognition, vol. 149, pp. 0 , (ISSN 0031-3203 1873-5142 ), doi: https://doi.org/10.1016/j.patcog.2023.110229 , 2024. Scientific article

Harald Lykke Joakimsen; Iver Martinsen; Luigi Tommaso Luppino; Andrew McDonald; Scott Hosking; et al. Interrogating Sea Ice Predictability with Gradients IEEE Geoscience and Remote Sensing Letters, pp. 1 5 4 , doi: https://doi.org/10.1109/LGRS.2024.3366308 , 2024. Scientific article

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, pp. 0 , doi: https://doi.org/10.1016/j.eswa.2024.123773 , 2024. Scientific article

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, vol. 48, pp. 384 400 17 , (ISSN 0364-9059 1558-1691 ), doi: https://doi.org/10.1109/JOE.2022.3226214 , 2023. Scientific article

Juan Emmanuel Johnson; Sigurd Eivindson Løkse; Gustau Camps-Valls; Karl Øyvind Mikalsen; Michael Kampffmeyer; et al. The Kernelized Taylor Diagram doi: https://doi.org/10.1007/978-3-031-17030-0_10 , 2023. Scientific chapter / article / conference article

Kristoffer Wickstrøm; Eirik Agnalt Østmo; Keyur Radiya; Karl Øyvind Mikalsen; Michael Kampffmeyer; et al. A clinically motivated self-supervised approach for content-based image retrieval of CT liver images Computerized Medical Imaging and Graphics, vol. 107, pp. 1 12 0 , (ISSN 0895-6111 1879-0771 ), doi: https://doi.org/10.1016/j.compmedimag.2023.102239 , 2023. Scientific article

Daniel Johansen Trosten; Rwiddhi Chakraborty; Sigurd Eivindson Løkse; Kristoffer Wickstrøm; Robert Jenssen; et al. Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings Computer Vision and Pattern Recognition, pp. 7527 7536 , (ISSN 1063-6919 ), doi: https://doi.org/10.1109/CVPR52729.2023.00727 , 2023. Scientific article

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, pp. 23976 23985 , (ISSN 1063-6919 ), doi: https://doi.org/10.1109/CVPR52729.2023.02296 , 2023. Scientific article

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, (ISSN 1520-6149 2379-190X ), doi: https://doi.org/10.1109/ICASSP49357.2023.10095856 , 2023. Scientific article

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, pp. 6 , (ISSN 1551-2541 2378-928X ), doi: https://doi.org/10.1109/MLSP55844.2023.10285978 , 2023. Scientific article

Kristoffer Wickstrøm; Sigurd Eivindson Løkse; Michael Kampffmeyer; Shujian Yu; José C. Príncipe; et al. Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy Entropy, vol. 25, pp. 1 21 0 , (ISSN 1099-4300 1099-4300 ), doi: https://doi.org/10.3390/e25060899 , 2023. Scientific article

Kristoffer Knutsen Wickstrøm; Sigurd Eivindson Løkse; Michael Christian Kampffmeyer; Shujian Yu; José C. Príncipe; et al. Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy Entropy, (ISSN 1099-4300 1099-4300 ), doi: https://doi.org/10.3390/e25060899 , 2023. Scientific article

Changkyu Choi; Michael Christian Kampffmeyer; Nils Olav Handegard; Arnt-Børre Salberg; Robert Jenssen; Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data 2023. Poster

Fredrik Emil Aspheim; Samuel Kuttner; Luigi Tommaso Luppino; Rune Sundset; Michael Christian Kampffmeyer; et al. Deep learning derived input-function in dynamic PET-imaging 2023. Lecture

Harald Lykke Joakimsen; Iver Martinsen; Luigi Tommaso Luppino; Robert Jenssen; "Explainable" IceNet with backpropagated gradients 2023. Poster

Deltaker i podcasten KA i KI 2023. Media participation

Robert Jenssen; On representation learning with information theoretic criteria and a new method for representation learning interpretability 2023. Scientific lecture

Robert Jenssen; XAI for representation learning 2023. Scientific lecture

Robert Jenssen; Deep learning in image analysis, graphs, and a new measure of statistical dependency between graphs 2023. Scientific lecture

Robert Jenssen; Self-supervised learning with XAI 2023. Scientific lecture

Robert Jenssen; XAI for representation learning 2023. Scientific lecture

Robert Jenssen; Information theoretic approaches: To clustering, graph neural networks and for investigating the dynamics of learning 2023. Scientific lecture

Robert Jenssen; Information Theory Meets Deep Learning 2023. Scientific lecture

Robert Jenssen; Kunstig intelligens i fremtidens helsetjenester 2023. Media interview

Robert Jenssen; Stortinget: Kunstig intelligens i helse 2023. Lecture popular

Robert Jenssen; A major Norwegian hub for AI research in health 2023. Lecture

Robert Jenssen; Kunstig intelligens i helse 2023. Lecture popular

Robert Jenssen; En offensiv offentlig politikk for kunstig intelligens i helsetjenesten 2023. Lecture popular

Robert Jenssen; Kunstig intelligens – Hva er det? Hvor kan det (mis)brukes 2023. Lecture popular

Robert Jenssen; NRK-intervju Arendalsuka 2023. Media interview

Fredrik Emil Aspheim; Luigi Tommaso Luppino; Michael Christian Kampffmeyer; Robert Jenssen; Rune Sundset; et al. Interpretable deep learning model for input function estimation in small-animal 18F-FDG PET imaging 2023. Scientific lecture

Ane Blazquez-Garcia; Kristoffer Knutsen Wickstrøm; Shujian Yu; Karl Øyvind Mikalsen; Ahcene Boubekki; et al. Selective Imputation for Multivariate Time Series Datasets with Missing Values IEEE Transactions on Knowledge and Data Engineering, vol. 35, pp. 9490 9501 11 , (ISSN 1041-4347 1558-2191 ), doi: https://doi.org/10.1109/TKDE.2023.3240858 , 2023. Scientific article

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 Medical Image Analysis, pp. 0 , doi: https://doi.org/10.1016/j.media.2023.102870 , 2023. Scientific article

Kristoffer Wickstrøm; Daniel Johansen Trosten; Sigurd Eivindson Løkse; Ahcene Boubekki; Karl Øyvind Mikalsen; et al. RELAX: Representation Learning Explainability International Journal of Computer Vision, pp. 1584 1610 26 , doi: https://doi.org/10.1007/s11263-023-01773-2 , 2023. Scientific article

Rogelio Andrade Mancisidor; Michael Christian Kampffmeyer; Kjersti Aas; Robert Jenssen; Discriminative multimodal learning via conditional priors in generative models Neural Networks, vol. 169, pp. 417 430 13 , (ISSN 0893-6080 1879-2782 ), doi: https://doi.org/10.1016/j.neunet.2023.10.048 , 2023. Scientific article

Kristoffer Vinther Olesen; Ahcene Boubekki; Michael Christian Kampffmeyer; Robert Jenssen; Anders Nymark Christensen; et al. A Contextually Supported Abnormality Detector for Maritime Trajectories Journal of Marine Science and Engineering, vol. 11, pp. 0 , (ISSN 2077-1312 2077-1312 ), doi: https://doi.org/10.3390/jmse11112085 , 2023. Scientific article

Robert Jenssen; rtg Pattern Recognition, (ISSN 0031-3203 1873-5142 ), 2022. Scientific article

Daniel Johansen Trosten; Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; RELAX: Representation Learning Explainability 2022. Poster

Daniel Johansen Trosten; Kristoffer Wickstrøm; Shujian Yu; Sigurd Eivindson Løkse; Robert Jenssen; et al. Deep Clustering with the Cauchy-Schwarz Divergence 2022. Scientific lecture

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Generating customer's credit behavior with deep generative models Knowledge-Based Systems, vol. 245, pp. 13 , (ISSN 0950-7051 1872-7409 ), doi: https://doi.org/10.1016/j.knosys.2022.108568 , 2022. Scientific article

Kristoffer Wickstrøm; Michael Kampffmeyer; Karl Øyvind Mikalsen; Robert Jenssen; Mixing up contrastive learning: Self-supervised representation learning for time series Pattern Recognition Letters, vol. 155, pp. 54 61 7 , (ISSN 0167-8655 1872-7344 ), doi: https://doi.org/10.1016/j.patrec.2022.02.007 , 2022. Scientific article

Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen; A self-guided anomaly detection-inspired few-shot segmentation network CEUR Workshop Proceedings, vol. 3271, (ISSN 1613-0073 1613-0073 ), 2022. Scientific article

Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen; A self-guided anomaly detection-inspired few-shot segmentation network CEUR Workshop Proceedings, vol. 3271, (ISSN 1613-0073 1613-0073 ), 2022. Scientific article

Suaiba Amina Salahuddin; Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen; A self-guided anomaly detection-inspired few-shot segmentation network CEUR Workshop Proceedings, vol. 3271, (ISSN 1613-0073 1613-0073 ), , 2022. Scientific article

Kristoffer Wickstrøm; Michael Kampffmeyer; Karl Øyvind Mikalsen; Robert Jenssen; Mixing up contrastive learning: Self-supervised representation learning for time series Pattern Recognition Letters, (ISSN 0167-8655 1872-7344 ), doi: https://doi.org/10.1016/j.patrec.2022.02.007 , 2022. Scientific article

Changkyu Choi; Shujian Yu; Michael Kampffmeyer; Arnt-Børre Salberg; Nils Olav Handegard; et al. Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior 2022. Poster

Shujian Yu; Francesco Alesiani; Wenzhe Yin; Robert Jenssen; Jose C. Principe; Principle of Relevant Information for Graph Sparsification Proceedings of Machine Learning Research (PMLR), vol. 180, pp. 2331 1241 17 , (ISSN 2640-3498 2640-3498 ), doi: https://doi.org/10.48550/arXiv.2206.00118 , 2022. Scientific article

Kristoffer Wickstrøm; Juan Emmanuel Johnson; Sigurd Eivindson Løkse; Gusatu Camps-Valls; Karl Øyvind Mikalsen; et al. The Kernelized Taylor Diagram Communications in Computer and Information Science, vol. 1650, pp. 125 131 7 , (ISSN 1865-0929 1865-0937 ), doi: https://doi.org/10.1007/978-3-031-17030-0_10 , 2022. Scientific article

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, vol. 43, pp. 3509 3535 26 , (ISSN 0143-1161 1366-5901 ), doi: https://doi.org/10.1080/01431161.2022.2098078 , 2022. Scientific article

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. Poster

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. Poster

Srishti Gautam; Marina Marie-Claire Hohne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer; Artifact Detection with Prototypical Relevance Propagation 2022. Poster

Srishti Gautam; Ahcene Boubekki; Stine Hansen; Suaiba Amina Salahuddin; Robert Jenssen; et al. ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model Advances in Neural Information Processing Systems, pp. 28 , doi: https://doi.org/10.48550/arXiv.2210.08151 , 2022. Scientific article

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, pp. 5 , doi: https://doi.org/10.1109/ISBI52829.2022.9761651 , 2022. Scientific article

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 Pattern Recognition, pp. 13 , doi: https://doi.org/10.1016/j.patcog.2022.109172 , 2022. Scientific article

Kristoffer Wickstrøm; Juan Emmanuel Johnson; Sigurd Eivindson Løkse; Gusatu Camps-Valls; Karl Øyvind Mikalsen; et al. The Kernelized Taylor Diagram 2022. Scientific lecture

Kristoffer Wickstrøm; Eirik Agnalt Østmo; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; Explaining representations for medical image retrieval 2022. Scientific lecture

Samuel Kuttner; Luigi Tommaso Luppino; Kristoffer Wickstrøm; Nils Thomas Doherty Midtbø; Seyed Esmaeil Dorraji; et al. Deep learning derived input function in dynamic 18F-FDG PET imaging of mice 2022. Scientific lecture

Luigi Tommaso Luppino; Mads Adrian Hansen; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; et al. Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images IEEE Transactions on Neural Networks and Learning Systems, pp. 13 , doi: https://doi.org/10.1109/TNNLS.2022.3172183 , 2022. Scientific article

Stine Hansen; Srishti Gautam; Robert Jenssen; Michael Kampffmeyer; Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels Medical Image Analysis, pp. 12 , doi: https://doi.org/10.1016/j.media.2022.102385 , 2022. Scientific article

Kristoffer Knutsen Wickstrøm; Daniel Johansen Trosten; Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; et al. RELAX: Representation Learning Explainability 2022. Poster

Kristoffer Knutsen Wickstrøm; Karl Oyvind Mikalsen; Michael Kampffmeyer; Arthur Revhaug; Robert Jenssen; Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series IEEE journal of biomedical and health informatics, vol. 25, pp. 2435 2444 9 , (ISSN 2168-2194 2168-2208 ), doi: https://doi.org/10.1109/JBHI.2020.3042637 , 2021. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; International Journal of Remote Sensing, vol. 42, pp. 6184 6208 , (ISSN 0143-1161 1366-5901 ), doi: https://doi.org/10.1080/01431161.2021.1936267 , 2021. Scientific article

Daniel Johansen Trosten; Robert Jenssen; Michael Kampffmeyer; Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective Proceedings of the Northern Lights Deep Learning Workshop, vol. 2, (ISSN 2703-6928 ), doi: https://doi.org/10.7557/18.5709 , 2021. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; PAGNet Models for The 2nd Agriculture-Vision Challenges CVPR 2021 , 2021. Scientific lecture

Changkyu Choi; Michael Kampffmeyer; Nils Olav Handegard; Arnt Børre Salberg; Olav Brautaset; et al. Semi-supervised target classification in multi-frequency echosounder data ICES Journal of Marine Science, vol. 78, pp. 2615 2627 12 , (ISSN 1054-3139 1095-9289 ), doi: https://doi.org/10.1093/icesjms/fsab140 , 2021. Scientific article

Nils Olav Handegard; Line Eikvil; Robert Jenssen; Michael Kampffmeyer; Arnt Børre Salberg; et al. Machine Learning + Marine Science: Critical Role of Partnerships in Norway Journal of Ocean Technology, vol. 16, pp. 1 9 8 , (ISSN 1718-3200 1718-3219 ), , 2021. Article journal

Changkyu Choi; Michael Kampffmeyer; Nils Olav Handegard; Arnt Børre Salberg; Line Eikvil; et al. Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data 2021. Poster

Michael Kampffmeyer; Robert Jenssen; Karl Øyvind Mikalsen; Sigurd Eivindson Løkse; Towards Explainable Representation Learning 2021. Lecture

Robert Jenssen; Anne H Schistad Solberg; Line Eikvil; Norge er verdensledende på bildeanalyse med kunstig intelligens 2021. Media interview

Robert Jenssen; Spearheading AI research and innovation in Norway 2021. Lecture

Robert Jenssen; Hvilken rolle kan kunstig intelligens ha i et kvinnehelseperspektiv? 2021. Lecture

Sigurd Eivindson Løkse; Michael Kampffmeyer; Robert Jenssen; Karl Øyvind Mikalsen; Towards Explainable Representation Learning 2021. Lecture

Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; Towards Explainable Representation Learning 2021. Lecture

Stine Hansen; Srishti Gautam; Robert Jenssen; Michael Kampffmeyer; Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision 2021. Scientific lecture

Ahcene Boubekki; Jonas Nordhaug Myhre; Luigi Tommaso Luppino; Karl Øyvind Mikalsen; Arthur Revhaug; et al. Clinically relevant features for predicting the severity of surgical site infections IEEE journal of biomedical and health informatics, (ISSN 2168-2194 2168-2208 ), doi: https://doi.org/10.1109/JBHI.2021.3121038 , 2021. Article journal

Kristoffer Knutsen Wickstrøm; Karl Øyvind Mikalsen; Michael Kampffmeyer; Arthur Revhaug; Robert Jenssen; Uncertainty-Aware Deep Ensembles for Explainable Time Series Prediction 2021. Scientific lecture

Kristoffer Knutsen Wickstrøm; Michael Kampffmeyer; Robert Jenssen; Advances in explainable DL & how to model uncertainty in explainability 2021. Scientific lecture

Kristoffer Knutsen Wickstrøm; Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; Towards Explainable Representation Learning 2021. Scientific lecture

Ahcene Boubekki; Michael Kampffmeyer; Ulf Brefeld; Robert Jenssen; Joint optimization of an autoencoder for clustering and embedding. Machine Learning, pp. 1901 1937 , doi: https://doi.org/10.1007/s10994-021-06015-5 , 2021. Scientific article

Daniel Johansen Trosten; Sigurd Eivindson Løkse; Robert Jenssen; Michael Kampffmeyer; Reconsidering Representation Alignment for Multi-View Clustering Computer Vision and Pattern Recognition, pp. 1255 1265 , doi: https://doi.org/10.1109/CVPR46437.2021.00131 , 2021. Scientific article

Luigi Tommaso Luppino; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; Sebastiano Bruno Serpico; et al. Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection IEEE Transactions on Geoscience and Remote Sensing, pp. 22 , doi: https://doi.org/10.1109/TGRS.2021.3056196 , 2021. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Dense dilated convolutions merging network for land cover classification IEEE Transactions on Geoscience and Remote Sensing, vol. 58, pp. 6309 6320 , (ISSN 0196-2892 1558-0644 ), doi: https://doi.org/10.1109/TGRS.2020.2976658 , 2020. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; MSCG-Net Models for The 1st Agriculture-Vision Challenge CVPR 2020 , 2020. Scientific lecture

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; MSCG-Net with Adaptive Class Weighting Loss for Semantic Segmentation , 2020. Scientific lecture

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Deep generative models for reject inference in credit scoring Knowledge-Based Systems, vol. 196, pp. 17 , (ISSN 0950-7051 1872-7409 ), doi: https://doi.org/10.1016/j.knosys.2020.105758 , 2020. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Multi-View Self-Constructing Graph Convolutional Networks With Adaptive Class Weighting Loss for Semantic Segmentation pp. 199 205 7 , doi: https://doi.org/10.1109/CVPRW50498.2020.00030 , 2020. Scientific chapter / article / conference article

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Learning latent representations of bank customers with the Variational Autoencoder Expert systems with applications, vol. 164, pp. 13 , (ISSN 0957-4174 1873-6793 ), doi: https://doi.org/10.1016/j.eswa.2020.114020 , 2020. Scientific article

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Learning latent representations of bank customers with the Variational Autoencoder Expert Systems With Applications, vol. 164, pp. 11 , (ISSN 0957-4174 1873-6793 ), doi: https://doi.org/10.1016/j.eswa.2020.114020 , 2020. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; SCG-Net for Semantic Labeling , 2020. Scientific lecture

Karl Øyvind Mikalsen; Cristina Soguero-Ruiz; Robert Jenssen; A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs (ISSN 9783030533519 ), 2020. Scientific anthology / conference series

Shujian Yu; Kristoffer Knutsen Wickstrøm; Robert Jenssen; Jose Principe; Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration IEEE Transactions on Neural Networks and Learning Systems, (ISSN 2162-237X 2162-2388 ), doi: https://doi.org/10.1109/TNNLS.2020.2968509 , 2020. Scientific article

Changkyu Choi; Filippo Maria Bianchi; Michael Kampffmeyer; Robert Jenssen; Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks Proceedings of the Northern Lights Deep Learning Workshop, (ISSN 2703-6928 ), doi: https://doi.org/10.7557/18.5136 , 2020. Scientific article

Mang Tik Chiu; Xu Xingqiang; Kai Wang; Jennifer Hobbs; Naira Hovakimyan; et al. The 1st Agriculture-Vision Challenge: Methods and Results pp. 212 218 , doi: https://doi.org/10.1109/CVPRW50498.2020.00032 , 2020. Scientific chapter / article / conference article

Michael Kampffmeyer; Robert Jenssen; Karl Øyvind Mikalsen; Arthur Revhaug; Uncertainty-Aware Deep Ensembles for Explainable Time Series Prediction 2020. Lecture

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg; Self-Constructing Graph Convolutional Networks for Semantic Labeling pp. 4 , doi: https://doi.org/10.1109/IGARSS39084.2020.9324719 , 2020. Scientific chapter / article / conference article

Stine Hansen; Samuel Kuttner; Michael Kampffmeyer; Tom-Vegard Markussen; Rune Sundset; et al. Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI Expert Systems With Applications, pp. 1 12 , doi: https://doi.org/10.1016/j.eswa.2020.114244 , 2020. Scientific article

Changkyu Choi; Michael Kampffmeyer; Robert Jenssen; A Robustness Analysis of Personalized Propagation of Neural Prediction , 2020. Poster

Changkyu Choi; Filippo Maria Bianchi; Michael Kampffmeyer; Robert Jenssen; Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks , 2020. Poster

Qinghui Liu; Michael C. Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images pp. 1 4 4 , doi: https://doi.org/10.1109/JURSE.2019.8809046 , 2019. Scientific chapter / article / conference article

Qinghui Liu; Michael C. Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; DDCM-Net for Semantic Mapping of Remote Sensing Images 2019. Poster

Michael C. Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt Børre Salberg; et al. Deep divergence-based approach to clustering Neural Networks, vol. 113, pp. 91 101 , (ISSN 0893-6080 1879-2782 ), doi: https://doi.org/10.1016/j.neunet.2019.01.015 , 2019. Scientific article

Filippo Maria Bianchi; Lorenzo Livi; Karl Øyvind Mikalsen; Michael C. Kampffmeyer; Robert Jenssen; Learning representations of multivariate time series with missing data Pattern Recognition, vol. 96:106973, pp. 1 11 , (ISSN 0031-3203 1873-5142 ), doi: https://doi.org/10.1016/j.patcog.2019.106973 , 2019. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network pp. 5041 5044 , doi: https://doi.org/10.1109/IGARSS.2019.8900082 , 2019. Scientific chapter / article / conference article

Qinghui Liu; Michael C. Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; DDCM Network for Semantic Mapping of Remote Sensing Images , 2019. Scientific lecture

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

Torgeir Brenn; Lars-Petter Gjøvik; Gunnar Ljosdahl Rasmussen; Tony Bauna; Michael Kampffmeyer; et al. Operationalizing Ship Detection Using Deep Learning , 2019. Scientific lecture

Kristoffer Knutsen Wickstrøm; Michael C. Kampffmeyer; Robert Jenssen; Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps Medical Image Analysis, doi: https://doi.org/10.1016/j.media.2019.101619 , 2019. Scientific article

Daniel Johansen Trosten; Andreas Storvik Strauman; Michael C. Kampffmeyer; Robert Jenssen; Recurrent Deep Divergence-based Clustering for Simultaneous Feature Learning and Clustering of Variable Length Time Series Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3257 3261 , doi: https://doi.org/10.1109/ICASSP.2019.8682365 , 2019. Scientific article

Qinghui Liu; Arnt Børre Salberg; Robert Jenssen; A COMPARISON OF DEEP LEARNING ARCHITECTURES FOR SEMANTIC MAPPING OF VERY HIGH RESOLUTION IMAGES , 2018. Poster

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Urban land cover classification with missing data modalities using deep convolutional neural networks IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, pp. 1758 1768 , (ISSN 1939-1404 2151-1535 ), doi: https://doi.org/10.1109/JSTARS.2018.2834961 , 2018. Scientific article

Michael C. Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi; The deep kernelized autoencoder Applied Soft Computing, vol. 71, pp. 816 825 , (ISSN 1568-4946 1872-9681 ), doi: https://doi.org/10.1016/j.asoc.2018.07.029 , 2018. Scientific article

Qinghui Liu; Arnt Børre Salberg; Robert Jenssen; A Comparison of Deep Learning Architectures for Semantic Mapping of Very High Resolution Images pp. 6943 6946 , doi: https://doi.org/10.1109/IGARSS.2018.8518533 , 2018. Scientific chapter / article / conference article

Sigurd Løkse; Filippo Maria Bianchi; Arnt Børre Salberg; Robert Jenssen; Spectral clustering using PCKID ? A probabilistic cluster kernel for incomplete data Lecture Notes in Computer Science (LNCS), vol. 10269 LNCS, pp. 431 442 , (ISSN 0302-9743 1611-3349 ), doi: https://doi.org/10.1007/978-3-319-59126-1_36 , 2017. Scientific article

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Urban land cover classification with missing data using deep convolutional neural networks pp. 5161 5164 4 , doi: https://doi.org/10.1109/IGARSS.2017.8128164 , 2017. Scientific chapter / article / conference article

Michael C. Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt Børre Salberg; et al. Deep divergence-based clustering doi: https://doi.org/10.1109/MLSP.2017.8168158 , 2017. Scientific chapter / article / conference article

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Urban land cover classification with missing data using deep convolutional neural networks , 2017. Scientific lecture

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Semantic Segmentation of Small Objects and Uncertainty in Urban Remote Sensing Images Using CNNs 2016. Poster

Michael C. Kampffmeyer; Arnt-Børre Salberg; Robert Jenssen; Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops, pp. 680 688 , (ISSN 2160-7508 ), doi: https://doi.org/10.1109/CVPRW.2016.90 , 2016. Scientific article

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks , 2016. Scientific lecture

Arnt Børre Salberg; Siri Øyen Larsen; Robert Jenssen; Classification of ocean surface slicks in hybrid-polarimetric SAR data Proceedings of SPIE, the International Society for Optical Engineering, vol. 9244, pp. 14 , (ISSN 0277-786X 1996-756X ), doi: https://doi.org/10.1117/12.2067474 , 2014. Scientific article

Arnt Børre Salberg; Robert Jenssen; Land-cover classification of partly missing data using support vector machines International Journal of Remote Sensing, vol. 33, pp. 4471 4481 11 , (ISSN 0143-1161 1366-5901 ), doi: https://doi.org/10.1080/01431161.2011.648378 , 2012. Scientific article

Arnt Børre Salberg; Jon Yngve Hardeberg; Robert Jenssen; Image Analysis. 16th Scandinavian Conference, SCIA 2009 Oslo Norway, June 2009. Proceedings (ISSN 3-642-02229-4 ), 2009. Scientific anthology / conference series

Arnt-Børre Salberg; Jon Yngve Hardeberg; Robert Jenssen; Image Analysis, 16th Scandinavian Conference Proceedings (SCIA), Oslo, Norway, June 2009, Springer Verlag Lecture Notes in Computer Science, LNCS 5575 (ISSN 978-3-642-02229-6 ), 2009. Non fiction book