Robert Jenssen

Orcid: 0000-0002-7496-8474

According to our database1, Robert Jenssen authored at least 147 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

Discriminative multimodal learning via conditional priors in generative models.
Neural Networks, January, 2024

Leveraging tensor kernels to reduce objective function mismatch in deep clustering.
Pattern Recognit., 2024

Interrogating Sea Ice Predictability With Gradients.
IEEE Geosci. Remote. Sens. Lett., 2024

LSNetv2: Improving weakly supervised power line detection with bipartite matching.
Expert Syst. Appl., 2024

Explaining time series models using frequency masking.
CoRR, 2024

Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications.
CoRR, 2024

Instruction-guided deidentification with synthetic test cases for Norwegian clinical text.
Proceedings of the Northern Lights Deep Learning Conference, 2024

Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Cauchy-Schwarz Divergence Information Bottleneck for Regression.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

MAP IT to Visualize Representations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement.
Medical Image Anal., October, 2023

Selective Imputation for Multivariate Time Series Datasets With Missing Values.
IEEE Trans. Knowl. Data Eng., September, 2023

RELAX: Representation Learning Explainability.
Int. J. Comput. Vis., June, 2023

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy.
Entropy, June, 2023

<i>This</i> looks <i>More</i> Like <i>that</i>: Enhancing Self-Explaining Models by Prototypical Relevance Propagation.
Pattern Recognit., April, 2023

The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making.
CoRR, 2023

A clinically motivated self-supervised approach for content-based image retrieval of CT liver images.
Comput. Medical Imaging Graph., 2023

View it Like a Radiologist: Shifted Windows for Deep Learning Augmentation Of CT Images.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Supercm: Revisiting Clustering for Semi-Supervised Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-Shot Learning with Hyperspherical Embeddings.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Clinically Relevant Features for Predicting the Severity of Surgical Site Infections.
IEEE J. Biomed. Health Informatics, 2022

Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection.
IEEE Trans. Geosci. Remote. Sens., 2022

Mixing up contrastive learning: Self-supervised representation learning for time series.
Pattern Recognit. Lett., 2022

Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels.
Medical Image Anal., 2022

Generating customer's credit behavior with deep generative models.
Knowl. Based Syst., 2022

BrainIB: Interpretable Brain Network-based Psychiatric Diagnosis with Graph Information Bottleneck.
CoRR, 2022

Principle of relevant information for graph sparsification.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Attention-guided Temporal Convolutional Network for Non-intrusive Load Monitoring.
Proceedings of the IEEE International Conference on Communications, 2022

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Kernelized Taylor Diagram.
Proceedings of the Nordic Artificial Intelligence Research and Development, 2022

Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

A self-guided anomaly detection-inspired few-shot segmentation network.
Proceedings of the Colour and Visual Computing Symposium 2022, 2022

2021
Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration.
IEEE Trans. Neural Networks Learn. Syst., 2021

Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series.
IEEE Trans. Neural Networks Learn. Syst., 2021

Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series.
IEEE J. Biomed. Health Informatics, 2021

Time series cluster kernels to exploit informative missingness and incomplete label information.
Pattern Recognit., 2021

LS-Net: fast single-shot line-segment detector.
Mach. Vis. Appl., 2021

Joint optimization of an autoencoder for clustering and embedding.
Mach. Learn., 2021

Learning latent representations of bank customers with the Variational Autoencoder.
Expert Syst. Appl., 2021

Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI.
Expert Syst. Appl., 2021

RELAX: Representation Learning Explainability.
CoRR, 2021

Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks.
CoRR, 2021

This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation.
CoRR, 2021

On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit.
CoRR, 2021

Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective.
Proceedings of the 2021 Northern Lights Deep Learning Workshop, 2021

Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms.
Proceedings of the IEEE International Conference on Consumer Electronics, 2021

Reconsidering Representation Alignment for Multi-View Clustering.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Measuring Dependence with Matrix-based Entropy Functional.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Dense Dilated Convolutions' Merging Network for Land Cover Classification.
IEEE Trans. Geosci. Remote. Sens., 2020

Multivariate Extension of Matrix-Based Rényi's $\alpha$α-Order Entropy Functional.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.
Medical Image Anal., 2020

Deep generative models for reject inference in credit scoring.
Knowl. Based Syst., 2020

SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation.
CoRR, 2020

A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs.
CoRR, 2020

Deep Image Clustering with Tensor Kernels and Unsupervised Companion Objectives.
CoRR, 2020

Self-Constructing Graph Convolutional Networks for Semantic Labeling.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

SEN: A Novel Feature Normalization Dissimilarity Measure for Prototypical Few-Shot Learning Networks.
Proceedings of the Computer Vision - ECCV 2020, 2020

A generic unfolding algorithm for manifolds estimated by local linear approximations.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020


2019
Noisy multi-label semi-supervised dimensionality reduction.
Pattern Recognit., 2019

Learning representations of multivariate time series with missing data.
Pattern Recognit., 2019

Deep divergence-based approach to clustering.
Neural Networks, 2019

Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels.
CoRR, 2019

Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data.
Comput. Math. Methods Medicine, 2019

Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images.
Proceedings of the Joint Urban Remote Sensing Event, 2019

Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Recurrent Deep Divergence-based Clustering for Simultaneous Feature Learning and Clustering of Variable Length Time Series.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Urban Land Cover Classification With Missing Data Modalities Using Deep Convolutional Neural Networks.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018

Robust clustering using a kNN mode seeking ensemble.
Pattern Recognit., 2018

Time series cluster kernel for learning similarities between multivariate time series with missing data.
Pattern Recognit., 2018

Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional.
CoRR, 2018

Segment-Based Credit Scoring Using Latent Clusters in the Variational Autoencoder.
CoRR, 2018

Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders.
CoRR, 2018

Understanding Convolutional Neural Network Training with Information Theory.
CoRR, 2018

An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples.
CoRR, 2018

The deep kernelized autoencoder.
Appl. Soft Comput., 2018

Uncertainty Modeling and interpretability in Convolutional Neural Networks for Polyp Segmentation.
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

A Comparison of Deep Learning Architectures for Semantic Mapping of Very High Resolution Images.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Ranking Using Transition Probabilities Learned from Multi-Attribute Data.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Bidirectional deep-readout echo state networks.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Learning compressed representations of blood samples time series with missing data.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Using multi-anchors to identify patients suffering from multimorbidities.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks.
Proceedings of the 2018 IEEE EMBS International Conference on Biomedical & Health Informatics, 2018

Towards deep anchor learning.
Proceedings of the 2018 IEEE EMBS International Conference on Biomedical & Health Informatics, 2018

2017
Recurrent Neural Networks for Short-Term Load Forecasting - An Overview and Comparative Analysis
Springer Briefs in Computer Science, Springer, ISBN: 978-3-319-70337-4, 2017

Optimized Kernel Entropy Components.
IEEE Trans. Neural Networks Learn. Syst., 2017

Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Bidirectional deep echo state networks.
CoRR, 2017

An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting.
CoRR, 2017

Training Echo State Networks with Regularization Through Dimensionality Reduction.
Cogn. Comput., 2017

Using anchors from free text in electronic health records to diagnose postoperative delirium.
Comput. Methods Programs Biomed., 2017

A Clustering Approach to Heterogeneous Change Detection.
Proceedings of the Image Analysis - 20th Scandinavian Conference, 2017

Spectral Clustering Using PCKID - A Probabilistic Cluster Kernel for Incomplete Data.
Proceedings of the Image Analysis - 20th Scandinavian Conference, 2017

Deep Kernelized Autoencoders.
Proceedings of the Image Analysis - 20th Scandinavian Conference, 2017

The time series cluster kernel.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Deep divergence-based clustering.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Critical echo state network dynamics by means of Fisher information maximization.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Temporal overdrive recurrent neural network.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Urban land cover classification with missing data using deep convolutional neural networks.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

Density ridge manifold traversal.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.
IEEE J. Biomed. Health Informatics, 2016

Predicting colorectal surgical complications using heterogeneous clinical data and kernel methods.
J. Biomed. Informatics, 2016

Multiplex visibility graphs to investigate recurrent neural networks dynamics.
CoRR, 2016

Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

Information Theoretic Clustering using a k-Nearest Neighbors-based Divergence Measure.
Proceedings of the Handbook of Pattern Recognition and Computer Vision, 5th Ed., 2016

2015
Spectral clustering with the probabilistic cluster kernel.
Neurocomputing, 2015

Consensus Clustering Using kNN Mode Seeking.
Proceedings of the Image Analysis - 19th Scandinavian Conference, 2015

Kernel covariance series smoothing.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

Sensitivity analysis of Gaussian processes for oceanic chlorophyll prediction.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

Data-driven Temporal Prediction of Surgical Site Infection.
Proceedings of the AMIA 2015, 2015

2014
Information theoretic clustering using a k-nearest neighbors approach.
Pattern Recognit., 2014

Mean Shift Spectral Clustering using Kernel Entropy Component Analysis.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Bootstrap resampling feature selection and Support Vector Machine for early detection of Anastomosis Leakage.
Proceedings of IEEE-EMBS International Conference on Biomedical and Health Informatics, 2014

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

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

A new information theoretic clustering algorithm using k-nn.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

Mean vector component analysis: A new approach to un-centered PCA for non-negative data.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

2012
Mixture weight influence on kernel entropy component analysis and semi-supervised learning using the Lasso.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

2011
A new scatter-based multi-class support vector machine.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Kernel entropy component analysis: New theory and semi-supervised learning.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Kernel entropy component analysis in remote sensing data clustering.
Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011

2010
Information theoretic clustering.
Scholarpedia, 2010

Kernel Entropy Component Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

A Reproducing Kernel Hilbert Space Framework for ITL.
Proceedings of the Information Theoretic Learning, 2010

Clustering with ITL Principles.
Proceedings of the Information Theoretic Learning, 2010

2009
Kernel Entropy Component Analysis Pre-images for Pattern Denoising.
Proceedings of the Image Analysis, 16th Scandinavian Conference, 2009

2008
Mean shift spectral clustering.
Pattern Recognit., 2008

A new information theoretic analysis of sum-of-squared-error kernel clustering.
Neurocomputing, 2008

2007
The Laplacian Classifier.
IEEE Trans. Signal Process., 2007

Information cut for clustering using a gradient descent approach.
Pattern Recognit., 2007

2006
Some Equivalences between Kernel Methods and Information Theoretic Methods.
J. VLSI Signal Process., 2006

Gaussianization: An Efficient Multivariate Density Estimation Technique for Statistical Signal Processing.
J. VLSI Signal Process., 2006

Spectral feature projections that maximize Shannon mutual information with class labels.
Pattern Recognit., 2006

The Cauchy-Schwarz divergence and Parzen windowing: Connections to graph theory and Mercer kernels.
J. Frankl. Inst., 2006

Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Information Theoretic Angle-Based Spectral Clustering: A Theoretical Analysis and an Algorithm.
Proceedings of the International Joint Conference on Neural Networks, 2006

2005
An information-theoretic perspective to kernel independent components analysis.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

The Laplacian spectral classifier.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering.
Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2005

2004
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Independent component analysis for texture segmentation.
Pattern Recognit., 2003

Information cut and information forces for clustering.
Proceedings of the NNSP 2003, 2003

Information Force Clustering Using Directed Trees.
Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003


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