Professor

Robert Jenssen

Professor / Machine Learning Department of Physics and Technology

77646493
41699612

robert.jenssen@uit.no

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Director, SFI Visual Intelligence. Visual Intelligence is a Centre for Research-based Innovation funded by the Research Council of Norway and a consortium of private and public partners. We are at the international forefront in deep learning research for complex image analysis. Please see

SFI Visual Intelligence

Twitter: @SFI_VI

Professor and Head of the UiT Machine Learning Group. Please see

UiT Machine Learning Group

Google Scholar Profile

Researcher profile in Cristin

Bianchi, Filippo Maria; Scardapane, Simone; Løkse, Sigurd; Jenssen, Robert. Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series. IEEE Transactions on Neural Networks and Learning Systems 2021; Volum 32 (5). ISSN 2162-237X.s 2169 - 2179.s doi: 10.1109/TNNLS.2020.3001377.

Choi, Changkyu; Kampffmeyer, Michael; Handegard, Nils Olav; Salberg, Arnt Børre; Brautaset, Olav; Eikvil, Line; Jenssen, Robert. Semi-supervised target classification in multi-frequency echosounder data. (Fulltekst: https://academic.oup.com/icesjms/advance-article/doi/10.1093/icesjms/fsab140/6348794 ICES Journal of Marine Science 2021. ISSN 1054-3139.s doi: 10.1093/icesjms/fsab140.

Nguyen, Van Nhan; Jenssen, Robert; Roverso, Davide. LS-Net: fast single-shot line-segment detector. Machine Vision and Applications 2021; Volum 32 (1). ISSN 0932-8092.s doi: 10.1007/s00138-020-01138-6.

Kuttner, Samuel; Wickstrøm, Kristoffer Knutsen; Lubberink, Mark; Tolf, Andreas; Burman, Joachim; Sundset, Rune; Jenssen, Robert; Appel, Lieuwe; Axelsson, Jan. Cerebral blood flow measurements with <sup>15</sup>O-water PET using a non-invasive machine-learning-derived arterial input function. Journal of Cerebral Blood Flow and Metabolism 2021. ISSN 0271-678X.s 1 - 13.s doi: 10.1177/0271678X21991393.

Trosten, Daniel Johansen; Jenssen, Robert; Kampffmeyer, Michael. Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective. Proceedings of the Northern Lights Deep Learning Workshop 2021; Volum 2.s doi: 10.7557/18.5709.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmentation of remote sensing images. International Journal of Remote Sensing 2021. ISSN 0143-1161.s doi: 10.1080/01431161.2021.1936267.

Luppino, Luigi Tommaso; Kampffmeyer, Michael; Bianchi, Filippo Maria; Moser, Gabriele; Serpico, Sebastiano Bruno; Jenssen, Robert; Anfinsen, Stian Normann. Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection. IEEE Transactions on Geoscience and Remote Sensing 2021. ISSN 0196-2892.s doi: 10.1109/TGRS.2021.3056196.

Mikalsen, Karl Øyvind; Ruiz, Cristina Soguero; Bianchi, Filippo Maria; Revhaug, Arthur; Jenssen, Robert. Time series cluster kernels to exploit informative missingness and incomplete label information. Pattern Recognition 2021. ISSN 0031-3203.s doi: 10.1016/j.patcog.2021.107896.

Luppino, Luigi Tommaso; Kampffmeyer, Michael; Bianchi, Filippo Maria; Moser, Gabriele; Serpico, Sebastian Bruno; Jenssen, Robert; Anfinsen, Stian Normann. Deep image translation with an affinity-based change prior for unsupervised multimodal change detection. IEEE Transactions on Geoscience and Remote Sensing 2021. ISSN 0196-2892.

Wickstrøm, Kristoffer Knutsen; Mikalsen, Karl Oyvind; Kampffmeyer, Michael; Revhaug, Arthur; Jenssen, Robert. Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series. IEEE journal of biomedical and health informatics 2021; Volum 25 (7). ISSN 2168-2194.s 2435 - 2444.s doi: 10.1109/JBHI.2020.3042637.

Kuttner, Samuel; Wickstrøm, Kristoffer Knutsen; Kalda, Gustav; Dorraji, Seyed Esmaeil; Martin-Armas, Montserrat; Oteiza, Ana; Jenssen, Robert; Fenton, Kristin Andreassen; Sundset, Rune; Axelsson, Jan. Machine learning derived input-function in a dynamic 18F-FDG PET study of mice. Biomedical Engineering & Physics Express 2020; Volum 6:015020. ISSN 2057-1976.s 1 - 13.s doi: 10.1088/2057-1976/ab6496.

Yu, Shujian; Giraldo, Luis Gonzalo Sánchez; Jenssen, Robert; Principe, Jose C.. Multivariate Extension of Matrix-Based Rényi's αα-Order Entropy Functional. IEEE Transactions on Pattern Analysis and Machine Intelligence 2020; Volum 42 (11). ISSN 0162-8828.s 2960 - 2966.s doi: 10.1109/TPAMI.2019.2932976.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt-Børre. Self-Constructing Graph Convolutional Networks for Semantic Labeling. IEEE 2020 ISBN 9781728163741.s doi: 10.1109/IGARSS39084.2020.9324719.

Chiu, Mang Tik; Xingqiang, Xu; Wang, Kai; Hobbs, Jennifer; Hovakimyan, Naira; Huang, Thomas S.; Shi, Honghui; Wei, Yunchao; Huang, Zilong; Schwing, Alexander; Brunner, Robert; Dozier, Ivan; Dozier, Wyatt; Ghandilyan, Karen; Wilson, David; Park, Hyunseong; Kim, Junhee; Kim, Sungho; Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre; Barbosa, Alexandre; Trevisan, Rodrigo; Zhao, Bingchen; Yu, Shaozuo; Yang, Siwei; Wang, Yin; Sheng, Hao; Chen, Xiao; Su, Jingyi; Rajagopal, Ram; Ng, Andrew; Huynh, Van Thong; Kim, Soo-Hyung; Na, In-Seop; Baid, Ujjwal; Innani, Shubham; Dutande, Prasad; Baheti, Bhakti; Talbar, Sanjay; Tang, Jianyu. The 1st Agriculture-Vision Challenge: Methods and Results. (Fulltekst: https://openaccess.thecvf.com/content_CVPRW_2020/html/w5/Chiu_The_1st_Agriculture-Vision_Challenge_Methods_and_Results_CVPRW_2020_paper.html IEEE 2020 (2020) ISBN 978-1-7281-9360-1. ISSN 2160-7508.s 212 - 218.s doi: 10.1109/CVPRW50498.2020.00032.

Choi, Changkyu; Bianchi, Filippo Maria; Kampffmeyer, Michael; Jenssen, Robert. Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks. Proceedings of the Northern Lights Deep Learning Workshop 2020; Volum 1.s doi: 10.7557/18.5136.

Yu, Shujian; Wickstrøm, Kristoffer Knutsen; Jenssen, Robert; Principe, Jose. Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration. IEEE Transactions on Neural Networks and Learning Systems 2020; Volum 32 (1). ISSN 2162-237X.s 436 - 442.s doi: 10.1109/TNNLS.2020.2968509.

Mikalsen, Karl Øyvind; Ruiz, Cristina Soguero; Jenssen, Robert. A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs. Springer 2020 (914) ISBN 9783030533519. ISSN 1860-949X.

Hansen, Stine; Kuttner, Samuel; Kampffmeyer, Michael; Markussen, Tom-Vegard; Sundset, Rune; Øen, Silje Kjærnes; Eikenes, Live; Jenssen, Robert. Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI. Expert Systems With Applications 2020; Volum 167:114244. ISSN 0957-4174.s 1 - 12.s doi: 10.1016/j.eswa.2020.114244.

Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert. Learning latent representations of bank customers with the Variational Autoencoder. Expert Systems With Applications 2020; Volum 164. ISSN 0957-4174.s doi: 10.1016/j.eswa.2020.114020.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. Multi-View Self-Constructing Graph Convolutional Networks With Adaptive Class Weighting Loss for Semantic Segmentation. (https://github.com/samleoqh/MSCG-Net) (Fulltekst: https://openaccess.thecvf.com/content_CVPRW_2020/papers/w5/Liu_Multi-View_Self-Constructing_Graph_Convolutional_Networks_With_Adaptive_Class_Weighting_Loss_CVPRW_2020_paper.pdf (Omtale: https://openaccess.thecvf.com/content_CVPRW_2020/html/w5/Liu_Multi-View_Self-Constructing_Graph_Convolutional_Networks_With_Adaptive_Class_Weighting_Loss_CVPRW_2020_paper.html) (Sammendrag: https://openaccess.thecvf.com/content_CVPRW_2020/html/w5/Liu_Multi-View_Self-Constructing_Graph_Convolutional_Networks_With_Adaptive_Class_Weighting_Loss_CVPRW_2020_paper.html) (Prosjekt: https://github.com/samleoqh/MSCG-Net) IEEE 2020 (2020) ISBN 978-1-7281-9360-1. ISSN 2160-7508.s 199 - 205.s doi: 10.1109/CVPRW50498.2020.00030.

Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert. Deep generative models for reject inference in credit scoring. Knowledge-Based Systems 2020; Volum 196. ISSN 0950-7051.s doi: 10.1016/j.knosys.2020.105758.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. Dense dilated convolutions merging network for land cover classification. (Fulltekst: https://ieeexplore.ieee.org/document/9027099 (Omtale: https://ieeexplore.ieee.org/document/9027099) IEEE Transactions on Geoscience and Remote Sensing 2020; Volum 58 (9). ISSN 0196-2892.s 6309 - 6320.s doi: 10.1109/TGRS.2020.2976658.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network. (Omtale: https://ieeexplore.ieee.org/document/8900082/) IEEE 2019 (2019) ISBN 978-1-5386-9154-0. ISSN 2153-6996.s 5041 - 5044.s doi: 10.1109/IGARSS.2019.8900082.

Wickstrøm, Kristoffer Knutsen; Kampffmeyer, Michael C.; Jenssen, Robert. Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps. Medical Image Analysis 2019. ISSN 1361-8415.s doi: 10.1016/j.media.2019.101619.

Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre. Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images. (Fulltekst: https://arxiv.org/abs/1908.11799v1 (Omtale: https://arxiv.org/abs/1908.11799v1) IEEE 2019 ISBN 978-1-7281-0009-8.s 1 - 4.s doi: 10.1109/JURSE.2019.8809046.

Trosten, Daniel Johansen; Strauman, Andreas Storvik; Kampffmeyer, Michael C.; Jenssen, Robert. 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 2019; Volum 2019-May. ISSN 1520-6149.s 3257 - 3261.s doi: 10.1109/ICASSP.2019.8682365.

Bianchi, Filippo Maria; Livi, Lorenzo; Mikalsen, Karl Øyvind; Kampffmeyer, Michael C.; Jenssen, Robert. Learning representations of multivariate time series with missing data. Pattern Recognition 2019; Volum 96:106973. ISSN 0031-3203.s 1 - 11.s doi: 10.1016/j.patcog.2019.106973.

Nguyen, van Nhan; Jenssen, Robert; Roverso, Davide. Intelligent Monitoring and Inspection of Power Line Components Powered by UAVs and Deep Learning. IEEE Power and Energy Technology Systems Journal 2019; Volum 6 (1). ISSN 2332-7707.s 11 - 21.s doi: 10.1109/JPETS.2018.2881429.

Kocbek, Primoz; Fijacko, Nino; Ruiz, Cristina Soguero; Mikalsen, Karl Øyvind; Maver, Uros; Brzan, Petra Povalej; Stozer, Andraz; Jenssen, Robert; Skrøvseth, Stein Olav; Stiglic, Gregor. Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data. Computational & Mathematical Methods in Medicine 2019; Volum 2019. ISSN 1748-670X.s doi: 10.1155/2019/2059851.

Mikalsen, Karl Øyvind; Soguero-Ruiz, Cristina; Bianchi, Filippo Maria; Jenssen, Robert. Noisy multi-label semi-supervised dimensionality reduction. Pattern Recognition 2019; Volum 90. ISSN 0031-3203.s 257 - 270.s doi: 10.1016/j.patcog.2019.01.033.

Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Livi, Lorenzo; Salberg, Arnt Børre; Jenssen, Robert. Deep divergence-based approach to clustering. Neural Networks 2019; Volum 113. ISSN 0893-6080.s 91 - 101.s doi: 10.1016/j.neunet.2019.01.015.

Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert. Urban land cover classification with missing data modalities using deep convolutional neural networks. (Fulltekst: https://arxiv.org/abs/1709.07383 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2018; Volum 11 (6). ISSN 1939-1404.s 1758 - 1768.s doi: 10.1109/JSTARS.2018.2834961.

Bianchi, Filippo Maria; Scardapane, Simone; Løkse, Sigurd; Jenssen, Robert. Bidirectional deep-readout echo state networks. (Fulltekst: https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2018-49.pdf 2018.s 425 - 430.

Bianchi, Filippo Maria; Mikalsen, Karl Øyvind; Jenssen, Robert. Learning compressed representations of blood samples time series with missing data. 2018.s doi: 10.1016/j.patcog.2019.106973.

Strauman, Andreas Storvik; Bianchi, Filippo Maria; Mikalsen, Karl Øyvind; Kampffmeyer, Michael C.; Soguero-Ruiz, Cristina; Jenssen, Robert. Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. IEEE 2018 ISBN 9781538624067.s 307 - 310.s doi: 10.1109/BHI.2018.8333430.

Hansen, Mads Adrian; Mikalsen, Karl Øyvind; Kampffmeyer, Michael C.; Soguero-Ruiz, Cristina; Jenssen, Robert. Towards deep anchor learning. IEEE 2018 ISBN 9781538624067.s 315 - 318.s doi: 10.1109/BHI.2018.8333432.

Mikalsen, Karl Øyvind; Soguero-Ruiz, Cristina; Mora-Jiménez, Inmaculada; Caballero López Fando, Isabel; Jenssen, Robert. Using multi-anchors to identify patients suffering from multimorbidities. IEEE 2018 ISBN 978-1-5386-5488-0.s 1514 - 1521.s doi: 10.1109/BIBM.2018.8621213.

Wickstrøm, Kristoffer Knutsen; Kampffmeyer, Michael C.; Jenssen, Robert. Uncertainty modeling and interpretability in convolutional neural networks for polyp segmentation. IEEE Signal Processing Society 2018 ISBN 978-1-5386-5477-4.s doi: 10.1109/MLSP.2018.8516998.

Liu, Qinghui; Salberg, Arnt Børre; Jenssen, Robert. A Comparison of Deep Learning Architectures for Semantic Mapping of Very High Resolution Images. (Fulltekst: http://publications.nr.no/1549971883/liu2018-igarss_paper.pdf (Omtale: https://ieeexplore.ieee.org/document/8518533) IEEE conference proceedings 2018 (2153-7003) ISBN 978-1-5386-7150-4. ISSN 2153-6996.s 6943 - 6946.s doi: 10.1109/IGARSS.2018.8518533.

Løkse, Sigurd; Jenssen, Robert. Ranking Using Transition Probabilities Learned from Multi-Attribute Data. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2018; Volum 2018-April. ISSN 1520-6149.s 2851 - 2855.s doi: 10.1109/ICASSP.2018.8462132.

Nguyen, van Nhan; Jenssen, Robert; Roverso, Davide. Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning. International Journal of Electrical Power & Energy Systems 2018; Volum 99. ISSN 0142-0615.s 107 - 120.s doi: 10.1016/j.ijepes.2017.12.016.

Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Jenssen, Robert; Livi, Lorenzo. The deep kernelized autoencoder. Applied Soft Computing 2018; Volum 71. ISSN 1568-4946.s 816 - 825.s doi: 10.1016/j.asoc.2018.07.029.

Løkse, Sigurd; Bianchi, Filippo Maria; Jenssen, Robert. Training Echo State Networks with Regularization Through Dimensionality Reduction. Cognitive Computation 2017; Volum 9 (3). ISSN 1866-9956.s 364 - 378.s doi: 10.1007/s12559-017-9450-z.

Mikalsen, Karl Øyvind; Bianchi, Filippo Maria; Ruiz, Cristina Soguero; Jenssen, Robert. Time series cluster kernel for learning similarities between multivariate time series with missing data. (Fulltekst: https://www.sciencedirect.com/science/article/pii/S0031320317304843 Pattern Recognition 2017; Volum 76. ISSN 0031-3203.s 569 - 581.s doi: 10.1016/j.patcog.2017.11.030.

Mikalsen, Karl Øyvind; Bianchi, Filippo Maria; Ruiz, Cristina Soguero; Jenssen, Robert. The time series cluster kernel. IEEE Signal Processing Society 2017 ISBN 978-1-5090-6341-3.

Bianchi, Filippo Maria; Livi, Lorenzo; Jenssen, Robert; Alippi, Cesare. Critical echo state network dynamics by means of Fisher information maximization. IEEE 2017 (2017) ISBN 978-1-5090-6182-2. ISSN 2161-4393.s 852 - 858.s doi: 10.1109/IJCNN.2017.7965941.

Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Livi, Lorenzo; Salberg, Arnt Børre; Jenssen, Robert. Deep divergence-based clustering. (Fulltekst: http://ieeexplore.ieee.org/document/8168158/ IEEE Signal Processing Society 2017 ISBN 978-1-5090-6341-3.s doi: 10.1109/MLSP.2017.8168158.

Bianchi, Filippo Maria; Kampffmeyer, Michael C.; Maiorino, Enrico; Jenssen, Robert. Temporal overdrive recurrent neural network. IEEE 2017 (2017) ISBN 978-1-5090-6182-2. ISSN 2161-4393.s 4275 - 4282.s doi: 10.1109/IJCNN.2017.7966397.

Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert. Urban land cover classification with missing data using deep convolutional neural networks. (Fulltekst: http://ieeexplore.ieee.org/document/8128164/ IEEE 2017 ISBN 978-1-5090-4951-6.s 5161 - 5164.s doi: 10.1109/IGARSS.2017.8128164.

Myhre, Jonas Nordhaug; Kampffmeyer, Michael C.; Jenssen, Robert. Density ridge manifold traversal. IEEE conference proceedings 2017 (2017) ISBN 978-1-5090-4117-6. ISSN 1520-6149.s 2342 - 2346.s doi: 10.1109/ICASSP.2017.7952575.

Myhre, Jonas Nordhaug; Jenssen, Robert; Mikalsen, Karl Øyvind; Løkse, Sigurd. Robust clustering using a kNN mode seeking ensemble. (Fulltekst: https://www.sciencedirect.com/science/article/pii/S0031320317304776 (Prosjekt: site.uit.no/ml/ og http://site.uit.no/reinforcementlearning/) Pattern Recognition 2017; Volum 76. ISSN 0031-3203.s 491 - 505.s doi: 10.1016/j.patcog.2017.11.023.

Mikalsen, Karl Øyvind; Ruiz, Cristina Soguero; Jensen, Kasper; Hindberg, Kristian; Gran, Mads; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Skrøvseth, Stein Olav; Godtliebsen, Fred; Jenssen, Robert. Using anchors from free text in electronic health records to diagnose postoperative delirium. Computer Methods and Programs in Biomedicine 2017; Volum 152. ISSN 0169-2607.s 105 - 114.s doi: 10.1016/j.cmpb.2017.09.014.

Luppino, Luigi Tommaso; Anfinsen, Stian Normann; Moser, Gabriele; Jenssen, Robert; Bianchi, Filippo Maria; Serpico, Sebastian Bruno; Mercier, Gregoire. A clustering approach to heterogeneous change detection. (Fulltekst: https://link.springer.com/chapter/10.1007/978-3-319-59129-2_16 Springer 2017 (10270) ISBN 978-3-319-59128-5. ISSN 0302-9743.s 181 - 192.s doi: 10.1007/978-3-319-59129-2_16.

Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Jenssen, Robert; Livi, Lorenzo. Deep kernelized autoencoders. Lecture Notes in Computer Science (LNCS) 2017; Volum 10269 LNCS. ISSN 0302-9743.s 419 - 430.s doi: 10.1007/978-3-319-59126-1_35.

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

Bianchi, Filippo Maria; Livi, Lorenzo; Alippi, Cesare; Jenssen, Robert. Multiplex visibility graphs to investigate recurrent neural network dynamics. Scientific Reports 2017; Volum 7. ISSN 2045-2322.s 1 - 13.s doi: 10.1038/srep44037.

Soguero-Ruiz, Cristina; Hindberg, Kristian; Mora-Jimenez, Inmaculada; Rojo-Álvarez, José Luis; Skrøvseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim Erlend; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert. Predicting colorectal surgical complications using heterogeneous clinical data and kernel methods. Journal of Biomedical Informatics 2016; Volum 61. ISSN 1532-0464.s 87 - 96.s doi: 10.1016/j.jbi.2016.03.008.

Kampffmeyer, Michael C.; Salberg, Arnt-Børre; Jenssen, Robert. 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 2016. ISSN 2160-7508.s 680 - 688.s doi: 10.1109/CVPRW.2016.90.

Blix, Katalin; Camps-Valls, Gustau; Jenssen, Robert. Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2016; Volum 10 (4). ISSN 1939-1404.s 1265 - 1277.s doi: 10.1109/JSTARS.2016.2641583.

Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gómez-Chova, Luis; Camps-Valls, Gustau. Optimized Kernel Entropy Components. IEEE Transactions on Neural Networks and Learning Systems 2016; Volum 28 (6). ISSN 2162-237X.s 1466 - 1472.s doi: 10.1109/TNNLS.2016.2530403.

Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Álvarez, José Luis; Skrøvseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim Erlend; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert. Support vector feature selection for early detection of anastomosis leakage from bag-of-words in electronic health records. IEEE journal of biomedical and health informatics 2016; Volum 20 (5). ISSN 2168-2194.s 1404 - 1415.s doi: 10.1109/JBHI.2014.2361688.

Soguero-Ruiz, Cristina; Wang, Fei; Jenssen, Robert; Augestad, Knut Magne; Álvarez, JL; Jiménez, Inmaculada Mora; Lindsetmo, Rolv-Ole; Skrøvseth, Stein Olav. Data-driven Temporal Prediction of Surgical Site Infection. AMIA Annual Symposium Proceedings 2015. ISSN 1559-4076.

Soguero-Ruiz, Cristina; Jenssen, Robert. Kernel covariance series smoothing. IEEE Workshop on Machine Learning for Signal Processing 2015; Volum 2015-November. ISSN 2161-0363.s 1 - 6.s doi: 10.1109/MLSP.2015.7324380.

Izquierdo-Verdiguier, Emma; Jenssen, Robert; Gómez-Chova, Luis; Camps-Valls, Gustavo. Spectral clustering with the probabilistic cluster kernel. Neurocomputing 2015; Volum 149. ISSN 0925-2312.s 1299 - 1304.s doi: 10.1016/j.neucom.2014.08.068.

Myhre, Jonas Nordhaug; Mikalsen, Karl Øyvind; Løkse, Sigurd; Jenssen, Robert. Consensus Clustering Using kNN Mode Seeking. Springer 2015; Volum 9127 (19) ISBN 978-3-319-19665-7. ISSN 0302-9743.s 175 - 186.s doi: 10.1007/978-3-319-19665-7_15.

Vikjord, Vidar Vangen; Jenssen, Robert. Information theoretic clustering using a k-nearest neighbors approach. Pattern Recognition 2014; Volum 47 (9). ISSN 0031-3203.s 3070 - 3081.s doi: 10.1016/j.patcog.2014.03.018.

Salberg, Arnt Børre; Larsen, Siri Øyen; Jenssen, Robert. Classification of ocean surface slicks in hybrid-polarimetric SAR data. Proceedings of SPIE, the International Society for Optical Engineering 2014; Volum 9244. ISSN 0277-786X.s doi: 10.1117/12.2067474.

Jenssen, Robert; Vikjord, Vidar Vangen. A new information theoretic clustering algorithm based on k-nn. IEEE Workshop on Machine Learning for Signal Processing 2013. ISSN 2161-0363.s 1 - 6.s doi: 10.1109/MLSP.2013.6661968.

Jenssen, Robert. Mean vector component analysis: A New approach to un-centered PCA for non-negative data. IEEE Workshop on Machine Learning for Signal Processing 2013. ISSN 2161-0363.s 1 - 6.s doi: 10.1109/MLSP.2013.6661966.

Jenssen, Robert. Mean Vector Component Analysis for Visualization and Clustering of Nonnegative Data. IEEE Transactions on Neural Networks and Learning Systems 2013; Volum 24 (10). ISSN 2162-237X.s 1553 - 1564.s doi: 10.1109/TNNLS.2013.2262774.

Jenssen, Robert. Entropy-relevant dimensions in the kernel feature space. IEEE Signal Processing Magazine 2013; Volum 30 (4). ISSN 1053-5888.s 30 - 39.s doi: 10.1109/MSP.2013.2249692.

Gómez-Chova, Luis; Jenssen, Robert; Camps-Valls, Gustavo. Kernel Entropy Component Analysis for Remote Sensing Image Clustering. IEEE Geoscience and Remote Sensing Letters 2012; Volum 9 (2). ISSN 1545-598X.s 312 - 316.s doi: 10.1109/LGRS.2011.2167212.

Jenssen, Robert; Myhre, Jonas Nordhaug. MIXTURE WEIGHT INFLUENCE ON KERNEL ENTROPY COMPONENT ANALYSIS AND SEMI-SUPERVISED LEARNING USING THE LASSO. (Fulltekst: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6349814 IEEE Signal Processing Society 2012 (13117249) ISBN 978‐1‐4673‐1026‐0. ISSN 1551-2541.s 1 - 6.s doi: 10.1109/mlsp.2012.6349814.

Jenssen, Robert; Kloft, Marius; Zien, Alexander; Sonnenburg, Soeren; Müller, Klaus R.. A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines. PLOS ONE 2012; Volum 7 (10). ISSN 1932-6203.s doi: 10.1371/journal.pone.0042947.

Salberg, Arnt Børre; Jenssen, Robert. Land-cover classification of partly missing data using support vector machines. International Journal of Remote Sensing 2012; Volum 33 (14). ISSN 0143-1161.s 4471 - 4481.s doi: 10.1080/01431161.2011.648378.

Jenssen, Robert; Principe, J. C.; Xu, Jianwu; Paiva, Antonio. A Reproducing Kernel Kernel Hilbert Space Framework for ITL. (http://www.springerlink.com/content/k42m08/#section=685255&page=51&locus=95) Springer Science+Business Media B.V. 2010 ISBN 978-1-4419-1569-6.s 351 - 384.

Jenssen, Robert; Principe, J. C.; Gockay, E.; Rao, S.. Clustering with ITL Principles. (http://www.springer.com/engineering/signals/book/978-1-4419-1569-6) Springer Science+Business Media B.V. 2010 ISBN 978-1-4419-1569-6.s 263 - 298.

Jenssen, Robert. Kernel Entropy Component Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 2010; Volum 32 (5). ISSN 0162-8828.s 847 - 860.s doi: 10.1109/TPAMI.2009.100.

Jenssen, Robert. Information Theoretic Learning and Kernel Methods. (http://www.springer.com/computer/theoretical+computer+science/book/978-0-387-84815-0) Springer Science+Business Media B.V. 2009 ISBN 978-0-387-84815-0.s 209 - 230.

Jenssen, Robert; Storås, Ola Kvisle. Kernel Entropy Component Analysis Pre-Images for Pattern Denoising. (Omtale: http://www.springer.com/computer/image+processing/book/978-3-642-02229-6?changeHeader) Springer 2009 (16) ISBN 3-642-02229-4. ISSN 0302-9743.s 626 - 635.

Ozertem, Umut; Erdogmus, Deniz; Jenssen, Robert. Mean shift spectral clustering. Pattern Recognition 2008; Volum 41. ISSN 0031-3203.s 1924 - 1938.s doi: 10.1016/j.patcog.2007.09.009.

Jenssen, Robert; Erdogmus, Deniz; Hild, Kenneth; Principe, Jose; Eltoft, Torbjørn. Information Cut for Clustering using a Gradient Descent Approach. Pattern Recognition 2007; Volum 40. ISSN 0031-3203.s 796 - 806.

Jenssen, Robert; Erdogmus, Deniz; Principe, Jose C.; Eltoft, Torbjørn. The Laplacian classifier. IEEE Transactions on Signal Processing 2007; Volum 55. ISSN 1053-587X.s 3262 - 3271.s doi: 10.1109/TSP.2007.894391.

Ozertem, Umut; Erdogmus, Deniz; Jenssen, Robert. Spectral feature projections that maximize Shannon mutual information with class labels. Pattern Recognition 2006; Volum 39. ISSN 0031-3203.s 1241 - 1252.

Jenssen, Robert; Principe, Jose; Erdogmus, Deniz; Eltoft, Torbjørn. The Cauchy-Schwarz Divergence and Parzen Windowing: Connections to Graph Theory and Mercer Kernels. Journal of the Franklin Institute 2006; Volum 343. ISSN 0016-0032.s 614 - 629.

Jenssen, Robert; Eltoft, Torbjørn; Erdogmus, Deniz; Principe, Jose. Some Equivalences Between Kernel Methods and Information Theoretic Methods. Journal of VLSI Signal Processing Systems for Signal, Image and Video Technology 2006; Volum 45. ISSN 0922-5773.s 49 - 65.

Erdogmus, Deniz; Jenssen, Robert; Rao, Yadunandana; Principe, Jose. Gaussianization: An Efficient Multivariate Density Estimation Technique for Statistical Signal Processing. Journal of VLSI Signal Processing Systems for Signal, Image and Video Technology 2006; Volum 45. ISSN 0922-5773.s 67 - 83.

Jenssen, Robert; Erdogmus, Deniz; Hild, Kenneth E.; Principe, Jose c.; Eltoft, Torbjørn. Optimizing the Cauchy-Schwarz PDF distance for information theoretic, non-parametric clustering. Lecture Notes in Computer Science (LNCS) 2005; Volum 3757. ISSN 0302-9743.

Jenssen, Robert; Eltoft, Torbjørn. Independent Component Analysis for Texture Segmentation. Pattern Recognition 2003; Volum 36 (10). ISSN 0031-3203.s 2301 - 2315.

Bianchi, Filippo Maria; Maiorino, Enrico; Kampffmeyer, Michael C.; Rizzi, Antonello; Jenssen, Robert. Recurrent Neural Networks for Short-Term Load Forecasting: An Overview and Comparative Analysis. Springer 2017 (1) ISBN 978-3-319-70338-1. ISSN 2191-5768.

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

Salberg, Arnt Børre; Hardeberg, Jon Yngve; Jenssen, Robert. Image Analysis. 16th Scandinavian Conference, SCIA 2009 Oslo Norway, June 2009. Proceedings. Springer 2009 (16) ISBN 3-642-02229-4. ISSN 0302-9743.s 626 - 635.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. PAGNet Models for The 2nd Agriculture-Vision Challenges CVPR 2021. CVPR 2021 Workshop on AGRICULTURE-VISION (Fulltekst: https://www.agriculture-vision.com/agriculture-vision-2021/program-schedule-2021 (Omtale: https://www.agriculture-vision.com/agriculture-vision-2021/program-schedule-2021) (Sammendrag: https://www.agriculture-vision.com/agriculture-vision-2021/program-schedule-2021) 2021-06-20 - 2021-06-21 2021.

Goodwin, Morten; Pettersen, Klas Henning; Jenssen, Robert. Episode 1 - Robert Jenssen forklarer kunstig intelligens innen helseforskning, computer vision og bildanalyse. (https://www.nora.ai/podcast/) 2020.

Choi, Changkyu; Kampffmeyer, Michael; Jenssen, Robert. A Robustness Analysis of Personalized Propagation of Neural Prediction. Northern Lights Deep Learning Workshop (NLDL) 2020 2020-01-19 - 2020-01-21 2020.

Choi, Changkyu; Bianchi, Filippo Maria; Kampffmeyer, Michael; Jenssen, Robert. Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks. Northern Lights Deep Learning Workshop (NLDL) 2020 (Fulltekst: https://septentrio.uit.no/index.php/nldl/article/download/5136/5092 2020-01-19 - 2020-01-21 2020.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. SCG-Net for Semantic Labeling. IGARSS 2020 (Fulltekst: https://igarss2020.org/view_paper.php?PaperNum=2222 2020-09-26 - 2020-10-02 2020.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. MSCG-Net with Adaptive Class Weighting Loss for Semantic Segmentation. CVPR 2020 Workshop on AGRICULTURE-VISION (Fulltekst: https://drive.google.com/file/d/1zNRKn7OtlT3yIk42l12gEJqGE7gsSiKS/view (Prosjekt: https://github.com/samleoqh/MSCG-Net) 2020-06-14 - 2020-06-19 2020.

Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. MSCG-Net Models for The 1st Agriculture-Vision Challenge CVPR 2020. CVPR 2020 Workshop on AGRICULTURE-VISION (Fulltekst: https://www.agriculture-vision.com/agriculture-vision-2020/program-schedule (Omtale: https://www.agriculture-vision.com/agriculture-vision-2020/program-schedule) (Sammendrag: https://github.com/samleoqh/MSCG-Net) 2020-06-14 - 2020-06-19 2020.

Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre. DDCM Network for Semantic Mapping of Remote Sensing Images. NLDL2019: Northern Lights Deep Learning Workshop (Omtale: https://slides.com/brianliu/deck) 2019-01-08 - 2019-01-10 2019.

Brenn, Torgeir; Gjøvik, Lars-Petter; Rasmussen, Gunnar Ljosdahl; Bauna, Tony; Kampffmeyer, Michael; Jenssen, Robert; Anfinsen, Stian Normann. Operationalizing Ship Detection Using Deep Learning. Maritime Situational Awareness Workshop (MSAW 2019) (Fulltekst: https://www.cmre.nato.int/msaw-2019-home/msaw2019-papers/1398-msaw2019-brenn-operationalizingshipdetectionusingdeeplearning/file 2019-10-08 - 2019-10-10 2019.

Mikalsen, Karl Øyvind; Jenssen, Robert. Advancing Unsupervised and Weakly Supervised Learning with Emphasis on Data-Driven Healthcare. 2019.

Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre. Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network. IGARSS 2019 (Omtale: https://slides.com/brianliu/roadmapping) 2019-07-27 - 2019-08-02 2019.

Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre. DDCM-Net for Semantic Mapping of Remote Sensing Images. JURSE2019 -Joint Urban Remote Sensing Event 2019-05-22 - 2019-05-24 2019.

Kampffmeyer, Michael C.; Jenssen, Robert. Advancing Segmentation and Unsupervised Learning Within the Field of Deep Learning. 2018.

Liu, Qinghui; Salberg, Arnt Børre; Jenssen, Robert. A COMPARISON OF DEEP LEARNING ARCHITECTURES FOR SEMANTIC MAPPING OF VERY HIGH RESOLUTION IMAGES. 2018 International Geoscience and Remote Sensing Symposium (Fulltekst: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8518533 (Sammendrag: https://ieeexplore.ieee.org/document/8518533) 2018-07-22 - 2018-07-27 2018.

Os, Vibeke; Jenssen, Robert. Lager system i et kaos av digital informasjon. (Fulltekst: https://uit.no/nyheter/artikkel?p_document_id=501762 2017.

Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert. Urban land cover classification with missing data using deep convolutional neural networks. 2017 IEEE International Geoscience and Remote Sensing Symposium (Fulltekst: http://ieeexplore.ieee.org/document/8128164/ 2017-07-23 - 2017-07-28 2017.

Vikjord, Vidar Vangen; Jenssen, Robert. INFORMATION THEORETIC CLUSTERING USING A k-NEAREST NEIGHBORS-BASED DIVERGENCE MEASURE. 2016 ISBN 978-981-4656-52-8.s 69 - 88.s doi: 10.1142/9789814656535_0004.

Myhre, Jonas; Mikalsen, Karl Øyvind; Løkse, Sigurd; Jenssen, Robert. Robust Non-Parametric Mode Clustering. NIPS workshop on Adaptive and Scalable Nonparametric Methods in Machine Learning 2016-12-10 - 2016-12-10 2016.

Mikalsen, Karl Øyvind; Bianchi, Filippo Maria; Soguero-Ruiz, Cristina; Skrøvseth, Stein Olav; Lindsetmo, Rolv-Ole; Revhaug, Arthur; Jenssen, Robert. Learning similarities between irregularly sampled short multivariate time series from EHRs. 3rd International Workshop on Pattern Recognition for Healthcare Analytics at ICPR 2016 2016-12-04 - 2016-12-04 2016.

Myhre, Jonas Nordhaug; Jenssen, Robert; Erdogmus, Deniz; Shaker, Matineh; Kaba, M. Devrim. Geometric interpretation of density ridges.. Geometry in Machine Learning workshop at ICML 2016 2016-06-26 - 2016-06-26 2016.

Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert. Semantic Segmentation of Small Objects and Uncertainty in Urban Remote Sensing Images Using CNNs. CIFAR-CRM Deep Learning Summer School 2016 2016-08-07 - 2016.

Myhre, Jonas Nordhaug; Kampffmeyer, Michael C.; Jenssen, Robert. Ambient space manifold learning using density ridges. ICML2016 Workshop on Geometry in Machine Learning 2016-06-23 - 2016.

Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert. Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks. IEEE Conference on Computer Vision and Pattern Recognition Workshops (Fulltekst: http://www.cv-foundation.org/openaccess/content_cvpr_2016_workshops/w19/papers/Kampffmeyer_Semantic_Segmentation_of_CVPR_2016_paper.pdf 2016-07-01 - 2016.

Soguero-Ruiz, Cristina; Hindberg, Kristian; Mora-Jimenez, Inmaculada; Rojo-Alvarez, Jose Luis; Skrøvseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim Erlend; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert. Prediction of Surgical Complications using Heterogeneous Clinical Data and Kernel Methods. NIPS workshop on machine learning in healthcare 2015-12-10 - 2015.

Soguero-Ruiz, Cristina; Jenssen, Robert. Kernel Covariance Series Smoothing. IEEE Conf. Machine Learning for Signal Processing 2015-09-17 - 2015-09-20 2015.

Blix, Katalin; Camps-Valls, Gustavo; Jenssen, Robert. Sensitivity Analysis of Gaussian Processes for Oceanic Chlorophyll Prediction. IGARSS 2015-06-26 - 2015-07-01 2015.

Mikalsen, Karl Øyvind; Jenssen, Robert; Godtliebsen, Fred; Skrøvseth, Stein Olav; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Hindberg, Kristian; Soguero-Ruiz, Cristina; Jensen, Kasper; Gran, Mads. Predicting Postoperative Delirium Using Anchors.. NIPS 2015 Workshop on Machine Learning in Healthcare 2015-12-15 - 2015-12-15 2015.

Soguero-Ruiz, Cristina; Mora-Jimenez, Inmaculada; Rojo-Alvarez, Jose Luis; Hindberg, Kristian; Godtliebsen, Fred; Mortensen, Kim Erlend; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Skrøvseth, Stein Olav; Augestad, Knut Magne; Jenssen, Robert. Feature selection using Kernel Component Analysis For Early Detection Of Anastomosis Leakage. 2nd International Workshop on Pattern Recognition for Healthcare Analytics (Fulltekst: https://sites.google.com/site/iwprha2/proceedings 2014-08-24 - 2014-08-24 2014.

Agersborg, Jørgen Andreas; Jenssen, Robert. Mean Shift Spectral Clustering Using Kernel Entropy Component Analysis. IEEE International Workshop on Machine Learning for Signal Processing (Sammendrag: http://www.conwiz.dk/cgi-all/mlsp2014/view_abstract.pl?idno=82) 2014-09-21 - 2014-09-26 2014.

Soguero-Ruiz, Cristina; Skrøvseth, Stein Olav; Augestad, Knut Magne; Jenssen, Robert. Bootstrap resampling feature selection and Support Vector Machine for early detection of Anastomosis Leakage. Biomedical and Health Informatics (BHI), 2014 IEEE-EMBS International Conference on 2014-06-01 - 2014-06-04 2014.

Jenssen, Robert. Machine learning and applications at the University of Tromso. Steering Committee Meeting at the Univ Antwerp 2013-06-19 - 2013-06-19 2013.

Jenssen, Robert; Vikjord, Vidar. A new information theoretic clustering algorithm based on k-nn. IEEE Workshop on machine learning for signal processing 2013-09-22 - 2013-09-25 2013.

Jenssen, Robert. Mean vector component analysis: A New approach to un-centered PCA. IEEE Machine Learning for Signal Processing 2013-09-22 - 2013-09-25 2013.

Jenssen, Robert. Entropy-Relevant Dimensions in Kernel Feature Space. University College London, Center for Computational Statistics and Machine Learning Lunch Talk 2013-04-05 - 2013-04-05 2013.

Jenssen, Robert. Kernel Entropy Component Analysis: A Unifying View. Invited Talk DTU Informatics and the Signal Processing Chapter of the IEEE Denmark Section. 2012-11-09 - 2012-11-09 2012.

Jenssen, Robert. NST - IBM Workshop: Machine Learning @ UiT. NST - IBM Workshop 2012-11-01 - 2012-11-01 2012.

Jenssen, Robert. Machine Learning for Data Analysis @ UiT. Talk at the Norwegian Centre for Integrated Care and Telemedicine. 2012-06-20 - 2012.

Jenssen, Robert. Background on Information Theoretic Learning. Talk at the DTU Informatics (Technical University of Denmark) 2012-10-04 - 2012.

Myhre, Jonas Nordhaug; Jenssen, Robert. MIXTURE WEIGHT INFLUENCE ON KERNEL ENTROPY COMPONENT ANALYSIS AND SEMI-SUPERVISED LEARNING USING THE LASSO. IEEE Workshop in Machine Learning for Signal Processing 2012-09-23 - 2012-09-26 2012.

Jenssen, Robert. Kernel Entropy Component Analysis: New Theory and Semi-Supervised Learning. IEEE Workshop on Machine Learning for Signal Processing 2011-09-18 - 2011-09-21 2011.

Jenssen, Robert. Kernel Entropy Component Analysis. Invitert foredrag Technical University of Berlin 2011-08-05 - 2011.

Jenssen, Robert. Machine Learning @ UiT. Studentforeninga Momentum 2011-11-15 - 2011.

Gomez-Chova, Luis; Jenssen, Robert; Camps-Valls, Gustavo. Kernel Entropy Component Analysis in Remote Sensing Data Clustering. International Geoscience and Remote Sensing Symposium 2011-07-24 - 2011-07-29 2011.

Jenssen, Robert; Kloft, Marius; Sonnenburg, Soeren; Zien, Alexander; Muller, Klaus-Robert. A New Scatter-Based Multi-Class Support Vector Machine. IEEE Workshop on Machine Learning for Signal Processing 2011-09-18 - 2011-09-21 2011.

Jenssen, Robert. "Intelligente" læringssystemer: Fra leken Furby til spamfiltre til miljø. Science - who cares? 2010-09-02 - 2010.

Jenssen, Robert; Principe, J. C.. Information theoretic clustering. (http://www.scholarpedia.org/article/Information_theoretic_clustering) Scholarpedia 2010; Volum 5 (10): 5189. ISSN 1941-6016.s doi: 10.4249/scholarpedia.5189.

Jenssen, Robert. Maskinlæring for Dataanalyse: Eksempler på anvendelser, "close-up" på spamfilter og Google PageRank. Mat.-Nat. populærvitenskapelig foredragsserie 2008-02-01 - 2008-02-01 2008.

Jenssen, Robert. New Information Theoretic Learning and Kernel Methods. Keynote talk, NOBIM 2008 Conference 2008-06-05 - 2008-06-06 2008.

Jenssen, Robert. Maskinlæring for Dataanalyse: Eksempler på anvendelser, "close-up" på spamfilter og Google PageRank. Populærvitenskapelig forelesning i forbindelse med klassebesøk fra Honningsvåg på IFT 2008-02-06 - 2008-02-06 2008.

Jenssen, Robert. Indefinite Parzen Window for Spectral Clustering. IEEE Conference on Machine Learning for Signal Processing 2007-08-27 - 2007-08-29 2007.

Anfinsen, Stian Normann; Jenssen, Robert; Eltoft, Torbjørn. Spectral Clustering of Polarimetric SAR Data with Wishart Derived Distance Measure. Proc. 3rd Int. Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry (POLinSAR 2007) (Fulltekst: http://earth.esa.int/workshops/polinsar2007/papers/140_anfinsen.pdf 2007-01-22 - 2007-01-26 2007.

Jenssen, Robert; Eltoft, Torbjørn. An Information Theoretic Perspective to Kernel K-Means. IEEE Machine Learning for Signal Processing Conference 2006-09-06 - 2006-09-08 2006.

Anfinsen, Stian Normann; Jenssen, Robert; Eltoft, Torbjørn. Classification of Polarimetric SAR Data with an Information Theoretic Kernel Method. International Geoscience and Remote Sensing Symposium 2006-07-31 - 2006-08-04 2006.

Hild, Kenneth E.; Jenssen, Robert. Experimental Upper Bound for Convolutive Mixtures of Speech by Maximizing SIR. IEEE Machine Learning for Signal Processing Conference 2006-09-06 - 2006-09-08 2006.

Jenssen, Robert; Girolami, Mark; Eltoft, Torbjørn; Erdogmus, Deniz. Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm. Advances in Neural Information Processing Systems Conference 2006-12-03 - 2006-12-10 2006.

Jenssen, Robert; Erdogmus, Deniz; Principe, Jose; Eltoft, Torbjørn. Information Theoretic Angle-Based Spectral Clustering: A Theoretical Analysis and an Algorithm. International Joint Conference on Neural Networks 2006-07-16 - 2006-07-21 2006.

Anfinsen, Stian Normann; Jenssen, Robert. Presentasjon av Institutt for fysikk, Forskningstorget 2005. Forskningstorget 2005 2005-09-23 - 2005-09-24 2005.

Xu, Jianwu; Erdogmus, Deniz; Jenssen, Robert; Principe, Jose. An Information Theoretic Perspective to Kernel Independent Component Analysis. International Conference on Acoustics, Speech and Signal Processing 2005-03-16 - 2005-03-23 2005.

Jenssen, Robert; Erdogmus, Deniz; Principe, Jose; Eltoft, Torbjørn. The Laplacian Spectral Classifier. International Conference on Acoustics, Speech and Signal Processing 2005-03-16 - 2005-03-23 2005.

Jenssen, Robert; Erdogmus, Deniz; Hild, Kenneth; Principe, Jose; Eltoft, Torbjørn. Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-Parametric Clustering. Energy Minimization Methods in Computer Vision and Pattern Recognition 2005-11-09 - 2005-11-11 2005.

Jenssen, Robert; Erdogmus, Deniz; Principe, Jose; Eltoft, Torbjørn. Towards a Unification of Information Theoretic Learning and Kernel Methods. Machine Learning for Signal Processing 2004-01-29 - 2004-10-01 2004.

Jenssen, Robert. The Information Cut and Graph Spectral Clustering. Invited Talk at the Computational NeuroEngineering Laboratory, University of Florida 2004-03-03 - 2004-03-03 2004.

Jenssen, Robert; Erdogmus, Deniz; Principe, Jose; Eltoft, Torbjørn. The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space. Neural Information Processing Systems 2004-12-08 - 2004-12-13 2004.

Jenssen, Robert. Fysikk som Rocker: Multikonsert og hjernesignaler. Forskningstorget 2004 2004-09-18 - 2004-09-18 2004.

Jenssen, Robert. Fysikk som Rocker: Multikonsert og hjernesignaler. Forskningstorget 2004 2004-09-17 - 2004-09-17 2004.

Erdogmus, Deniz; Jenssen, Robert; Rao, Yadunandana; Principe, Jose. Multivariate Density Estimation with Optimal Marginal Parzen Density Estimation and Gaussianization. Machine Learning for Signal Processing 2004-09-29 - 2004-10-01 2004.

Jenssen, Robert; Eltoft, Torbjørn; Principe, Jose. Information Theoretic Spectral Clustering. International Joint Conference on Neural Networks 2004-07-25 - 2004-07-29 2004.

Jenssen, Robert; Eltoft, Torbjørn; Principe, Jose. Information Theoretic Clustering: A Unifying Review of Three Recent Algorithms. Nordic Symposium on Signal Processing 2004-06-09 - 2004-06-11 2004.

Jenssen, Robert. Fysikk som Rocker. Forskningstorget 2003 2003-09-19 - 2003-09-19 2003.

Hanssen, Alfred; Jenssen, Robert; Hindberg, Kristian. Fysikk som rocker. 2003.

Jenssen, Robert; Erdogmus, Deniz; Hild, Kenneth E.; Principe, Jose c.; Eltoft, Torbjørn. Information Force Clustering using Directed Trees. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition 2003-07-07 - 2003-07-09 2003.

Jenssen, Robert; Principe, Jose c.; Eltoft, Torbjørn. Cauchy-Schwartz pdf Divergence Measure for non-Parametric Clustering. Norwgian Symposium in Signal Processing 2003 2003-10-02 - 2004-10-04 2003.

Jenssen, Robert; Erdogmus, Deniz; Hild, Kenneth E.; Principe, Jose c.; Eltoft, Torbjørn. Clustering using Renyi's Entropy. Int. Joint Conference on Neural Networks 2003-07-20 - 2003-07-24 2003.

Jenssen, Robert; Principe, Jose c.; Eltoft, Torbjørn. Information Cut and Information Forces for Clustering. IEEE Int. Workshop on Neural Networks for Signal Processing 2003-09-17 - 2003-09-19 2003.

Erdogmus, Deniz; Fontela-romero, O.; Principe, Jose; Alonso-betanzos, A.; Castillo, E.; Jenssen, Robert. Accurate Initialization of Neural Network Weights by Backpropagation of the Desired Response. Int'l. Joint Conference on Neural Networks 2003-07-20 - 2003-07-24 2003.

Jenssen, Robert; Eltoft, Torbjørn. ICA Filter Bank for Segmentation of Textured Images. Int. Workshop on Independent Component Analysis and Blind Signal Separation 2003-04-01 - 2003-04-04 2003.

Jenssen, Robert. Fysikk som Rocker. Forskningstorget 2003 2003-09-20 - 2003-09-20 2003.

Jenssen, Robert. Institutt for Fysikk - Presentasjon til Ungdomskoleelever. Presentasjon av Institutt for Fysikk 2002-06-14 - 2002-06-14 2002.

Jenssen, Robert. Taleseparering, CD-spiller og multikonsert. Åpen dag, Institutt for Fysikk, 2002 2002-01-08 - 2002-01-08 2002.

Jenssen, Robert. Taleseparering. Åpen dag, Institutt for Fysikk 2002 2002-01-07 - 2002-01-07 2002.

Jenssen, Robert. CD-spilleren og Multikonsert. Presentasjon av Institutt for Fysikk 2002-03-11 - 2002-03-11 2002.

Jenssen, Robert. CD-spilleren og Multikonsert. Presentasjon av Institutt for Fysikk 2002-03-06 - 2002-03-06 2002.

Jenssen, Robert. CD-spilleren og Multikonsert. Kreativ uke 2002 2002-03-12 - 2002-03-12 2002.

Jenssen, Robert. CD-spillerens virkemåte. Ingeniørenes dag 2001 2001-09-19 - 2001-09-19 2001.

Jenssen, Robert. CD-spillerens virkemåte. Ingeniørenes dag 2001 2001-09-29 - 2001-09-29 2001.

Jenssen, Robert; Øigård, Tor Arne; Eltoft, Torbjørn; Hanssen, Alfred. Sparse code shrinkage based on the normal inverse Gaussian density model. Proceedings of NORSIG'01 2001-10-01 - 2001-10-01 2001.

Jenssen, Robert; Øigård, Tor Arne; Eltoft, Torbjørn; Hanssen, Alfred. Sparse code shrinkage based on the normal inverse Gaussian density model. 3rd Int. Conf. on Independent Component Analysis and Blind Signal Separation 2001-12-09 - 2001-12-12 2001.