Information Force Clustering Using Directed Trees. - Robert Jenssen; Deniz Erdogmus; Kenneth E. Hild II; José Carlos Príncipe; Torbjørn Eltoft (EMMCVPR, 2003)

Accurate initialization of neural network weights by backpropagation of the desired response. - Deniz Erdogmus; Oscar Fontenla-Romero; José C. Príncipe; Amparo Alonso-Betanzos; Enrique F. Castillo; Robert Jenssen (IJCNN, 2003)

Clustering using Renyi's entropy. - Robert Jenssen; Kenneth E. Hild II; Deniz Erdogmus; José C. Príncipe; Torbjørn Eltoft (IJCNN, 2003)

Information cut and information forces for clustering. - Robert Jenssen; José C. Príncipe; Torbjørn Eltoft (NNSP, 2003)

Independent component analysis for texture segmentation. - Robert Jenssen; Torbjørn Eltoft (Pattern Recognit., 2003)

Information theoretic spectral clustering. - Robert Jenssen; Torbjørn Eltoft; José C. Príncipe (IJCNN, 2004)

The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space. - Robert Jenssen; Deniz Erdogmus; José Carlos Príncipe; Torbjørn Eltoft (NIPS, 2004)

Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering. - Robert Jenssen; Deniz Erdogmus; Kenneth E. Hild II; José Carlos Príncipe; Torbjørn Eltoft (EMMCVPR, 2005)

The Laplacian spectral classifier. - Robert Jenssen; Deniz Erdogmus; José C. Príncipe; Torbjørn Eltoft (ICASSP (5), 2005)

An information-theoretic perspective to kernel independent components analysis. - Jian-Wu Xu; Deniz Erdogmus; Robert Jenssen; José C. Príncipe (ICASSP (5), 2005)

Information Theoretic Angle-Based Spectral Clustering: A Theoretical Analysis and an Algorithm. - Robert Jenssen; Deniz Erdogmus; José C. Príncipe (IJCNN, 2006)

Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm. - Robert Jenssen; Torbjørn Eltoft; Mark A. Girolami; Deniz Erdogmus (NIPS, 2006)

The Cauchy-Schwarz divergence and Parzen windowing: Connections to graph theory and Mercer kernels. - Robert Jenssen; José C. Príncipe; Deniz Erdogmus; Torbjørn Eltoft (J. Frankl. Inst., 2006)

Spectral feature projections that maximize Shannon mutual information with class labels. - Umut Ozertem; Deniz Erdogmus; Robert Jenssen (Pattern Recognit., 2006)

Gaussianization: An Efficient Multivariate Density Estimation Technique for Statistical Signal Processing. - Deniz Erdogmus; Robert Jenssen; Yadunandana N. Rao; José C. Príncipe (J. VLSI Signal Process., 2006)

Some Equivalences between Kernel Methods and Information Theoretic Methods. - Robert Jenssen; Torbjørn Eltoft; Deniz Erdogmus; José C. Príncipe (J. VLSI Signal Process., 2006)

Information cut for clustering using a gradient descent approach. - Robert Jenssen; Deniz Erdogmus; Kenneth E. Hild II; José C. Príncipe; Torbjørn Eltoft (Pattern Recognit., 2007)

The Laplacian Classifier. - Robert Jenssen; Deniz Erdogmus; José C. Príncipe; Torbjørn Eltoft (IEEE Trans. Signal Process., 2007)

A new information theoretic analysis of sum-of-squared-error kernel clustering. - Robert Jenssen; Torbjørn Eltoft (Neurocomputing, 2008)

Mean shift spectral clustering. - Umut Ozertem; Deniz Erdogmus; Robert Jenssen (Pattern Recognit., 2008)

Kernel Entropy Component Analysis Pre-images for Pattern Denoising. - Robert Jenssen; Ola Storås (SCIA, 2009)

Clustering with ITL Principles. - Robert Jenssen; Sudhir Rao (Information Theoretic Learning, 2010)

A Reproducing Kernel Hilbert Space Framework for ITL. - Jian-Wu Xu; Robert Jenssen; António R. C. Paiva; Il Park 002 (Information Theoretic Learning, 2010)

Kernel Entropy Component Analysis. - Robert Jenssen (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

Information theoretic clustering. - Robert Jenssen; José Carlos Príncipe (Scholarpedia, 2010)

Kernel entropy component analysis in remote sensing data clustering. - Luis Gómez-Chova; Robert Jenssen; Gustavo Camps-Valls (IGARSS, 2011)

Kernel entropy component analysis: New theory and semi-supervised learning. - Robert Jenssen (MLSP, 2011)

A new scatter-based multi-class support vector machine. - Robert Jenssen; Marius Kloft; Sören Sonnenburg; Alexander Zien; Klaus-Robert Müller (MLSP, 2011)

Mixture weight influence on kernel entropy component analysis and semi-supervised learning using the Lasso. - Jonas Nordhaug Myhre; Robert Jenssen (MLSP, 2012)

Mean vector component analysis: A new approach to un-centered PCA for non-negative data. - Robert Jenssen (MLSP, 2013)

A new information theoretic clustering algorithm using k-nn. - Vidar Vikjord; Robert Jenssen (MLSP, 2013)

Entropy-Relevant Dimensions in the Kernel Feature Space: Cluster-Capturing Dimensionality Reduction. - Robert Jenssen (IEEE Signal Process. Mag., 2013)

Mean Vector Component Analysis for Visualization and Clustering of Nonnegative Data. - Robert Jenssen (IEEE Trans. Neural Networks Learn. Syst., 2013)

Bootstrap resampling feature selection and Support Vector Machine for early detection of Anastomosis Leakage. - Cristina Soguero-Ruíz; Kristian Hindberg; José Luis Rojo-Álvarez; Stein Olav Skrøvseth; Fred Godtliebsen; Kim Mortensen; Arthur Revhaug; Rolv-Ole Lindsetmo; Inmaculada Mora-Jiménez; Knut Magne Augestad; Robert Jenssen (BHI, 2014)

Mean Shift Spectral Clustering using Kernel Entropy Component Analysis. - Jørgen Andreas Agersborg; Robert Jenssen (MLSP, 2014)

Information theoretic clustering using a k-nearest neighbors approach. - Vidar Vikjord; Robert Jenssen (Pattern Recognit., 2014)

Data-driven Temporal Prediction of Surgical Site Infection. - Cristina Soguero-Ruíz; Fei Wang 001; Robert Jenssen; Knut Magne Augestad; José Luis Rojo-Álvarez; Inmaculada Mora-Jiménez; Rolv-Ole Lindsetmo; Stein Olav Skrøvseth (AMIA, 2015)

Sensitivity analysis of Gaussian processes for oceanic chlorophyll prediction. - Katalin Blix; Gustau Camps-Valls; Robert Jenssen (IGARSS, 2015)

Kernel covariance series smoothing. - Cristina Soguero-Ruíz; Robert Jenssen (MLSP, 2015)

Consensus Clustering Using kNN Mode Seeking. - Jonas Nordhaug Myhre; Karl Øyvind Mikalsen; Sigurd Løkse; Robert Jenssen (SCIA, 2015)

Spectral clustering with the probabilistic cluster kernel. - Emma Izquierdo-Verdiguier; Robert Jenssen; Luis Gómez-Chova; Gustavo Camps-Valls (Neurocomputing, 2015)

Information Theoretic Clustering using a k-Nearest Neighbors-based Divergence Measure. - Vidar V. Vikjord; Robert Jenssen (Handbook of Pattern Recognition and Computer Vision, 2016)

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)

Multiplex visibility graphs to investigate recurrent neural networks dynamics. - Filippo Maria Bianchi; Lorenzo Livi; Cesare Alippi; Robert Jenssen (CoRR, 2016)

Predicting colorectal surgical complications using heterogeneous clinical data and kernel methods. - Cristina Soguero-Ruíz; Kristian Hindberg; Inmaculada Mora-Jiménez; José Luis Rojo-Álvarez; Stein Olav Skrøvseth; Fred Godtliebsen; Kim Mortensen; Arthur Revhaug; Rolv-Ole Lindsetmo; Knut Magne Augestad; Robert Jenssen (J. Biomed. Informatics, 2016)

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records. - Cristina Soguero-Ruíz; Kristian Hindberg; José Luis Rojo-Álvarez; Stein Olav Skrøvseth; Fred Godtliebsen; Kim Mortensen; Arthur Revhaug; Rolv-Ole Lindsetmo; Knut Magne Augestad; Robert Jenssen (IEEE J. Biomed. Health Informatics, 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)

Critical echo state network dynamics by means of Fisher information maximization. - Filippo Maria Bianchi; Lorenzo Livi; Robert Jenssen; Cesare Alippi (IJCNN, 2017)

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

The time series cluster kernel. - Karl Øyvind Mikalsen; Filippo Maria Bianchi; Cristina Soguero-Ruíz; Robert Jenssen (MLSP, 2017)

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

Spectral Clustering Using PCKID - A Probabilistic Cluster Kernel for Incomplete Data. - Sigurd Løkse; Filippo Maria Bianchi; Arnt-Børre Salberg; Robert Jenssen (SCIA (1), 2017)

A Clustering Approach to Heterogeneous Change Detection. - Luigi Tommaso Luppino; Stian Normann Anfinsen; Gabriele Moser; Robert Jenssen; Filippo Maria Bianchi; Sebastiano B. Serpico; Grégoire Mercier (SCIA (2), 2017)

Using anchors from free text in electronic health records to diagnose postoperative delirium. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Kasper Jensen; Kristian Hindberg; Mads Gran; Arthur Revhaug; Rolv-Ole Lindsetmo; Stein Olav Skrøvseth; Fred Godtliebsen; Robert Jenssen (Comput. Methods Programs Biomed., 2017)

Training Echo State Networks with Regularization Through Dimensionality Reduction. - Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen (Cogn. Comput., 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)

Bidirectional deep echo state networks. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (CoRR, 2017)

Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation. - Katalin Blix; Gustau Camps-Valls; Robert Jenssen (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017)

Optimized Kernel Entropy Components. - Emma Izquierdo-Verdiguier; Valero Laparra; Robert Jenssen; Luis Gómez-Chova; Gustau Camps-Valls (IEEE Trans. Neural Networks Learn. Syst., 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)

Using multi-anchors to identify patients suffering from multimorbidities. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Inmaculada Mora-Jiménez; Isabel Caballero-López-Fando; Robert Jenssen (BIBM, 2018)

Learning compressed representations of blood samples time series with missing data. - Filippo Maria Bianchi; Karl Øyvind Mikalsen; Robert Jenssen (ESANN, 2018)

Bidirectional deep-readout echo state networks. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (ESANN, 2018)

Ranking Using Transition Probabilities Learned from Multi-Attribute Data. - Sigurd Løkse; Robert Jenssen (ICASSP, 2018)

A Comparison of Deep Learning Architectures for Semantic Mapping of Very High Resolution Images. - Qinghui Liu; Arnt-Børre Salberg; Robert Jenssen (IGARSS, 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)

An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Filippo Maria Bianchi; Arthur Revhaug; Robert Jenssen (CoRR, 2018)

Understanding Convolutional Neural Network Training with Information Theory. - Shujian Yu; Robert Jenssen; José C. Príncipe (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)

Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional. - Shujian Yu; Luis Gonzalo Sánchez Giraldo; Robert Jenssen; José C. Príncipe (CoRR, 2018)

Time series cluster kernel for learning similarities between multivariate time series with missing data. - Karl Øyvind Mikalsen; Filippo Maria Bianchi; Cristina Soguero-Ruíz; Robert Jenssen (Pattern Recognit., 2018)

Robust clustering using a kNN mode seeking ensemble. - Jonas Nordhaug Myhre; Karl Øyvind Mikalsen; Sigurd Løkse; Robert Jenssen (Pattern Recognit., 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)

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)

Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data. - Primoz Kocbek; Nino Fijacko; Cristina Soguero-Ruíz; Karl Øyvind Mikalsen; Uros Maver; Petra Povalej Brzan; Andraz Stozer; Robert Jenssen; Stein Olav Skrøvseth; Gregor Stiglic (Comput. Math. Methods Medicine, 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)

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)

Noisy multi-label semi-supervised dimensionality reduction. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Filippo Maria Bianchi; Robert Jenssen (Pattern Recognit., 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)

A generic unfolding algorithm for manifolds estimated by local linear approximations. - Jonas Nordhaug Myhre; Matineh Shaker; Mustafa Devrim Kaba; Robert Jenssen; Deniz Erdogmus (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)

A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; 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)

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)

Multivariate Extension of Matrix-Based Rényi's $ alpha$α-Order Entropy Functional. - Shujian Yu; Luis Gonzalo Sánchez Giraldo; Robert Jenssen; José C. Príncipe (IEEE Trans. Pattern Anal. Mach. Intell., 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)

Measuring Dependence with Matrix-based Entropy Functional. - Shujian Yu; Francesco Alesiani; Xi Yu; Robert Jenssen; José C. Príncipe (AAAI, 2021)

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

Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms. - Huamin Ren; Filippo Maria Bianchi; Jingyue Li; Rasmus L. Olsen; Robert Jenssen; Stian Normann Anfinsen (ICCE, 2021)

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

On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit. - Óscar Escudero-Arnanz; Joaquín Álvarez-Rodríguez; Karl Øyvind Mikalsen; Robert Jenssen; Cristina Soguero-Ruíz (CoRR, 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)

LS-Net: fast single-shot line-segment detector. - Van Nhan Nguyen; Robert Jenssen; Davide Roverso (Mach. Vis. Appl., 2021)

Time series cluster kernels to exploit informative missingness and incomplete label information. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Filippo Maria Bianchi; Arthur Revhaug; Robert Jenssen (Pattern Recognit., 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)

Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (IEEE Trans. Neural Networks Learn. Syst., 2021)

Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration. - Shujian Yu; Kristoffer Wickstrøm; Robert Jenssen; José C. Príncipe (IEEE Trans. Neural Networks Learn. Syst., 2021)

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

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)

Attention-guided Temporal Convolutional Network for Non-intrusive Load Monitoring. - Huamin Ren; Xiaomeng Su; Robert Jenssen; Jingyue Li; Stian Normann Anfinsen (SmartGridComm, 2022)

Principle of relevant information for graph sparsification. - Shujian Yu; Francesco Alesiani; Wenzhe Yin; Robert Jenssen; José C. Príncipe (UAI, 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)

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)

Clinically Relevant Features for Predicting the Severity of Surgical Site Infections. - Ahcène Boubekki; Jonas Nordhaug Myhre; Luigi Tommaso Luppino; Karl Øyvind Mikalsen; Arthur Revhaug; Robert Jenssen (IEEE J. Biomed. Health Informatics, 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)

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)

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)

Selective Imputation for Multivariate Time Series Datasets With Missing Values. - Ane Blázquez-García; Kristoffer Wickstrøm; Shujian Yu; Karl Øyvind Mikalsen; Ahcène Boubekki; Angel Conde; Usue Mori; Robert Jenssen; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 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)

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)

MAP IT to Visualize Representations. - Robert Jenssen (ICLR, 2024)

Cauchy-Schwarz Divergence Information Bottleneck for Regression. - Shujian Yu; Xi Yu; Sigurd Løkse; Robert Jenssen; José C. Príncipe (ICLR, 2024)

Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks. - Bjørn Leth Møller; Christian Igel; Kristoffer Knutsen Wickstrøm; Jon Sporring; Robert Jenssen; Bulat Ibragimov (ICML, 2024)

Instruction-guided deidentification with synthetic test cases for Norwegian clinical text. - Jørgen Aarmo Lund; Karl Øyvind Mikalsen; Per Joel Burman; Ashenafi Zebene Woldaregay; Robert Jenssen (NLDL, 2024)

Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications. - Mingfei Lu; Shujian Yu; Robert Jenssen; Badong Chen (CoRR, 2024)

Explaining time series models using frequency masking. - Thea Brüsch; Kristoffer K. Wickstrøm; Mikkel N. Schmidt; Tommy S. Alstrøm; Robert Jenssen (CoRR, 2024)

FLEXtime: Filterbank learning for explaining time series. - Thea Brüsch; Kristoffer K. Wickstrøm; Mikkel N. Schmidt; Robert Jenssen; Tommy S. Alstrøm (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)

Interrogating Sea Ice Predictability With Gradients. - Harald L. Joakimsen; Iver Martinsen; Luigi Tommaso Luppino; Andrew McDonald 003; Scott Hosking; Robert Jenssen (IEEE Geosci. Remote. Sens. Lett., 2024)

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

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

Leveraging Foundation Model Adapters to Enable Robust and Semantic Underwater Exploration. - Changkyu Choi; Arangan Subramaniam; Nils Olav Handegard; Ali Ramezani-Kebrya; Robert Jenssen (NAIS, 2025)

FreqRISE: Explaining time series using frequency masking. - Thea Brüsch; Kristoffer Knutsen Wickstrøm; Mikkel N. Schmidt; Tommy Sonne Alstrøm; Robert Jenssen (NLDL, 2025)

NEMt: Fast Targeted Explanations for Medical Image Models via Neural Explanation Masks. - Bjørn Leth Møller; Sepideh Amiri; Christian Igel; Kristoffer Knutsen Wickstrøm; Robert Jenssen; Matthias Keicher; Mohammad Farid Azampour; Nassir Navab; Bulat Ibragimov (NLDL, 2025)

Investigating the Impact of Feature Reduction for Deep Learning-based Seasonal Sea Ice Forecasting. - Lars Uebbing; Harald L. Joakimsen; Luigi Tommaso Luppino; Iver Martinsen; Andrew McDonald 003; Kristoffer Knutsen Wickstrøm; Sébastien Lefèvre; Arnt-Børre Salberg; Scott Hosking; Robert Jenssen (NLDL, 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)

Generalized Cauchy-Schwarz divergence: Efficient estimation and applications in deep learning. - Mingfei Lu; Shujian Yu; Robert Jenssen; Badong Chen (Neurocomputing, 2025)

Guest Editorial: Special Issue on Information Theoretic Methods for the Generalization, Robustness, and Interpretability of Machine Learning. - Badong Chen; Shujian Yu; Robert Jenssen; José C. Príncipe; Klaus-Robert Müller (IEEE Trans. Neural Networks Learn. Syst., 2025)

Natural Language Processing for Electronic Health Records in Scandinavian Languages: Norwegian, Swedish, and Danish. - Ashenafi Zebene Woldaregay; Jørgen Aarmo Lund; Phuong Dinh Ngo; Mariyam Tayefi; Per Joel Burman; Stine Hansen; Martin Hylleholt Sillesen; Hercules Dalianis; Robert Jenssen; Lindsetmo Rolf Ole; Karl Øyvind Mikalsen (CoRR, 2025)

From Colors to Classes: Emergence of Concepts in Vision Transformers. - Teresa Dorszewski; Lenka Tetková; Robert Jenssen; Lars Kai Hansen; Kristoffer Knutsen Wickstrøm (CoRR, 2025)

Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders. - Rogelio Andrade Mancisidor; Robert Jenssen; Shujian Yu; 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)

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)

The Conditional Cauchy-Schwarz Divergence With Applications to Time-Series Data and Sequential Decision Making. - Shujian Yu; Hongming Li; Sigurd Løkse; Robert Jenssen; José C. Príncipe (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

BrainIB: Interpretable Brain Network-Based Psychiatric Diagnosis With Graph Information Bottleneck. - Kaizhong Zheng; Shujian Yu; Baojuan Li; Robert Jenssen; Badong Chen (IEEE Trans. Neural Networks Learn. Syst., 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)