Morten Mørup

发表

Karen Marie Sandø Ambrosen, Morten Mørup, Tim B. Dyrby, 2016 .

A deep learning approach to adherence detection for type 2 diabetics

Morten Mørup, Ali Mohebbi, Tinna B. Aradottir, 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Decomposing the time-frequency representation of EEG using non-negative matrix and multi-way factorization

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2006 .

Difference-of-Convex optimization for variational kl-corrected inference in dirichlet process mixtures

Morten Mørup, Mikkel N. Schmidt, Rasmus Bonnevie, 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).

Tuning pruning in sparse non-negative matrix factorization

Lars Kai Hansen, Morten Mørup, 2009, 2009 17th European Signal Processing Conference.

Modeling latency and shape changes in trial based neuroimaging data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

Infinite Relational Modeling of Functional Connectivity in Resting State fMRI

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2010, NIPS.

The Missing Link: Predicting Connectomes from Noisy and Partially Observed Tract Tracing Data

Paul H. E. Tiesinga, Morten Mørup, Max Hinne, 2016 .

Bayesian latent feature modeling for modeling bipartite networks with overlapping groups

Morten Mørup, Mikkel N. Schmidt, Philip H. Jørgensen, 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

Multiplicative updates For Non-Negative Kernel SVM pdf

Vince D. Calhoun, Vamsi K. Potluru, Sergey M. Plis, 2009, ArXiv.

Predictive assessment of models for dynamic functional connectivity

Morten Mørup, Mikkel N. Schmidt, Søren Føns Vind Nielsen, 2018, NeuroImage.

Advances in Nonnegative Matrix and Tensor Factorization

Andrzej Cichocki, Paris Smaragdis, Morten Mørup, 2008, Comput. Intell. Neurosci..

Independent vector analysis for capturing common components in fMRI group analysis

Morten Mørup, Kasper Winther Andersen, Kristoffer Hougaard Madsen, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Simulation Environment for Guiding the Design of Contextual Personalization Systems in the Context of Hearing Aids

Morten Mørup, Jakob Eg Larsen, Michael Kai Petersen, 2020, UMAP.

Approximate L0 constrained non-negative matrix and tensor factorization

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2008, 2008 IEEE International Symposium on Circuits and Systems.

Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy

Vince D. Calhoun, Lars Kai Hansen, Morten Mørup, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Link prediction in weighted networks

David Kofoed Wind, Morten Mørup, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

Analysis of Conceptualization Patterns across Groups of People

Morten Mørup, Mikkel N. Schmidt, Kenji Araki, 2013, 2013 Conference on Technologies and Applications of Artificial Intelligence.

Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI Data

Morten Mørup, Vincent Beliveau, Georgios Papoutsakis, 2016, MCV/BAMBI@MICCAI.

Fast Assessment of Glycemic Control based on Continuous Glucose Monitoring Data

Morten Mørup, Ali Mohebbi, Henrik Bengtsson, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Shifted Independent Component Analysis

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2007, ICA.

Bayesian Community Detection

Morten Mørup, Mikkel N. Schmidt, M. Mørup, 2012, Neural Computation.

Nonparametric Bayesian clustering of structural whole brain connectivity in full image resolution

Morten Mørup, Tim B. Dyrby, Mikkel N. Schmidt, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

Unsupervised Knowledge Structuring: Application of Infinite Relational Models to the FCA Visualization

Morten Mørup, Mikkel N. Schmidt, Fumiko Kano Glückstad, 2013, 2013 International Conference on Signal-Image Technology & Internet-Based Systems.

A Bayesian Analysis of the Radioactive Releases of Fukushima

Morten Mørup, Ryota Tomioka, Ryota Tomioka, 2012, AISTATS.

Infinite non-negative matrix factorization

Morten Mørup, Mikkel N. Schmidt, Morten Mørup, 2010, 2010 18th European Signal Processing Conference.

Decomposition methods for unsupervised learning

Morten Mørup, M. Mørup, Morten Mørup, 2008 .

Probabilistic Sparse Non-negative Matrix Factorization

Morten Mørup, Jesper Løve Hinrich, 2018, LVA/ICA.

Testing a Model of Destination Image Formation: Application of Nonparametric Bayesian Relational Modeling to Destination Image Analysis

Morten Mørup, Mikkel N. Schmidt, Fumiko Kano Glückstad, 2018 .

Analysis of Chromatographic Data using the Probabilistic PARAFAC2

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2019, NeurIPS 2019.

Cross-categorization of legal concepts across boundaries of legal systems: in consideration of inferential links

Morten Mørup, Mikkel N. Schmidt, Fumiko Kano Glückstad, 2013, Artificial Intelligence and Law.

Discovering hierarchical structure in normal relational data

Morten Mørup, Mikkel N. Schmidt, Tue Herlau, 2014, 2014 4th International Workshop on Cognitive Information Processing (CIP).

Applications of tensor (multiway array) factorizations and decompositions in data mining

Morten Mørup, M. Mørup, Morten Mørup, 2011, WIREs Data Mining Knowl. Discov..

Archetypal Analysis for Modeling Multisubject fMRI Data

Morten Mørup, Kristoffer Hougaard Madsen, Nathan William Churchill, 2016, IEEE Journal of Selected Topics in Signal Processing.

Crowds, bluetooth, and rock'n'roll: understanding music festival participant behavior

Piotr Sapiezynski, Arkadiusz Stopczynski, Morten Mørup, 2013, PDM '13.

Efficient Multiplicative Updates for Support Vector Machines

Vince D. Calhoun, Vamsi K. Potluru, Sergey M. Plis, 2009, SDM.

SOFOMORE: Combined EEG source and forward model reconstruction

Ole Winther, Lars Kai Hansen, Morten Mørup, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Understanding Mindsets Across Markets, Internationally: A Public-Private Innovation Project for Developing a Tourist Data Analytic Platform

Morten Mørup, Mikkel N. Schmidt, Rasmus Bonnevie, 2018, 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC).

Modelling dense relational data

Lars Kai Hansen, Morten Mørup, Mikkel N. Schmidt, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

Scalable Tensor Factorizations for Incomplete Data pdf

Tamara G. Kolda, Morten Mørup, Daniel M. Dunlavy, 2010, ArXiv.

Correction: The missing link: Predicting connectomes from noisy and partially observed tract tracing data

Paul H. E. Tiesinga, Morten Mørup, Max Hinne, 2017, PLoS computational biology.

Quantifying functional connectivity in multi‐subject fMRI data using component models

Morten Mørup, Kristoffer Hougaard Madsen, Kristoffer H. Madsen, 2017, Human brain mapping.

Model Order Estimation for Independent Component Analysis of Epoched EEG Signals

Lars Kai Hansen, Morten Mørup, Peter Mondrup Rasmussen, 2008, BIOSIGNALS.

Feature-based Ontology Mapping from an Information Receivers’ Viewpoint

Morten Mørup, Fumiko Kano Glückstad, M. Mørup, 2016 .

Errata to “Bayesian Community Detection” (Neural Computation, Sept. 2012, Vol. 24, No. 9:2434–2456)

Morten Mørup, Mikkel N. Schmidt, 2014, Neural Computation.

Identification of Functional Clusters in the Striatum Using Infinite Relational Modeling

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2011, MLINI.

Modeling dynamic functional connectivity using a wishart mixture model

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2017, 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Modelling the structure of complex networks

Morten Mørup, Tue Herlau, M. Mørup, 2015 .

Analysis of Brain Data - Using Multi-Way Array Models on the EEG

Morten Mørup, 2005 .

Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation

Morten Mørup, Mikkel N. Schmidt, M. Mørup, 2006, ICA.

Large scale inference in the Infinite Relational Model: Gibbs sampling is not enough

Morten Mørup, Mikkel N. Schmidt, Kristoffer Jon Albers, 2013, 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

The influence of hyper-parameters in the infinite relational model

Morten Mørup, Mikkel N. Schmidt, Kristoffer Jon Albers, 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

Latent semantics as cognitive components

Lars Kai Hansen, Morten Mørup, Michael Kai Petersen, 2010, 2010 2nd International Workshop on Cognitive Information Processing.

Non-negative Tensor Factorization with missing data for the modeling of gene expressions in the Human Brain

Morten Mørup, Søren Føns Vind Nielsen, M. Mørup, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Nonparametric statistical structuring of knowledge systems using binary feature matches

Morten Mørup, Mikkel N. Schmidt, Fumiko Kano Glückstad, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Completely random measures for modelling block-structured sparse networks

Morten Mørup, Mikkel N. Schmidt, Tue Herlau, 2016, NIPS.

Bayesian and Non-linear Multi-way modelling

Morten Mørup, 2009 .

VARIATIONAL BAYESIAN PARTIALLY OBSERVED NON-NEGATIVE TENSOR FACTORIZATION

Morten Mørup, Kristoffer Hougaard Madsen, Søren Føns Vind Nielsen, 2018, 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP).

Infinite multiple membership relational modeling for complex networks

Lars Kai Hansen, Morten Mørup, Mikkel N. Schmidt, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

The missing link: Predicting connectomes from noisy and partially observed tract tracing data

Paul H. E. Tiesinga, Morten Mørup, Marcel van Gerven, 2016, bioRxiv.

The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI

Morten Mørup, Kristoffer Hougaard Madsen, Nathan William Churchill, 2016, Neural Computation.

Temporally intermittent communities in brain fMRI correlation networks

Sune Lehmann, Morten Mørup, Søren Føns Vind Nielsen, 2019, Appl. Netw. Sci..

Session MP7a: Processing of physiological signals

Morten Mørup, Nuri Firat Ince, 2011, ACSCC.

Comparing Structural Brain Connectivity by the Infinite Relational Model

Morten Mørup, Tim B. Dyrby, Mikkel N. Schmidt, 2013, 2013 International Workshop on Pattern Recognition in Neuroimaging.

The probabilistic tensor decomposition toolbox

Morten Mørup, Kristoffer Hougaard Madsen, Jesper Løve Hinrich, 2020, Mach. Learn. Sci. Technol..

Non-parametric co-clustering of large scale sparse bipartite networks on the GPU

Lars Kai Hansen, Morten Mørup, L. K. Hansen, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Unsupervised segmentation of task activated regions in fMRI

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2015, 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP).

Validation of structural brain connectivity networks: The impact of scanning parameters

Morten Mørup, Tim B. Dyrby, Mikkel N. Schmidt, 2020, NeuroImage.

Infinite von Mises–Fisher Mixture Modeling of Whole Brain fMRI Data

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2017, Neural Computation.

Joint Modelling of Structural and Functional Brain Networks

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2012, NIPS 2012.

Identifying modular relations in complex brain networks

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

Temporally Evolving Hierarchies in Networks

Morten Mørup, Mikkel N. Schmidt, Tue Herlau, 2012 .

Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2006, NeuroImage.

Large Scale GPU Based Inference for the Infinite Relational Model

Morten Mørup, L. K. Hansen, Toke Jansen Hansen, 2010, NIPS 2010.

Latent Causal Modelling of Neuroimaging Data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2009, NIPS 2009.

Transformation invariant sparse coding

Morten Mørup, Mikkel N. Schmidt, M. Mørup, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach

Ole Winther, Lars Kai Hansen, Morten Mørup, 2011, J. Signal Process. Syst..

Testing group differences in state transition structure of dynamic functional connectivity models

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2018, 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Probabilistic Tensor Train Decomposition

Morten Mørup, Jesper L. Hinrich, M. Mørup, 2019, 2019 27th European Signal Processing Conference (EUSIPCO).

Modeling Temporal Evolution and Multiscale Structure in Networks

Morten Mørup, Mikkel N. Schmidt, Tue Herlau, 2013, ICML.

Frequency constrained ShiftCP modeling of neuroimaging data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

Nonparametric Bayesian modeling of complex networks: an introduction

Morten Mørup, Mikkel N. Schmidt, M. Mørup, 2013, IEEE Signal Processing Magazine.

Variational group-PCA for intrinsic dimensionality determination in fMRI data

Morten Mørup, Kristoffer Hougaard Madsen, Søren Føns Vind Nielsen, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Shift-invariant multilinear decomposition of neuroimaging data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2008, NeuroImage.

Detecting hierarchical structure in networks

Lars Kai Hansen, Morten Mørup, Mikkel N. Schmidt, 2012, 2012 3rd International Workshop on Cognitive Information Processing (CIP).

Probabilistic PARAFAC2 pdf

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2018, ArXiv.

Algorithms for Sparse Nonnegative Tucker Decompositions

Lars Kai Hansen, Morten Mørup, L. K. Hansen, 2008, Neural Computation.

Scalable Tensor Factorizations with Missing Data

Tamara G. Kolda, Morten Mørup, Daniel M. Dunlavy, 2010, SDM.

Non-parametric Bayesian graph models reveal community structure in resting state fMRI

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2014, NeuroImage.

Scalable group level probabilistic sparse factor analysis

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Using connectomics for predictive assessment of brain parcellations

Morten Mørup, Tim B. Dyrby, Mikkel N. Schmidt, 2021, NeuroImage.

Supplementary materials [Code] to: Latent profile analysis of human values: What is the optimal number of clusters?

Eldad Davidov, Morten Mørup, Mikkel N. Schmidt, 2021 .

Early Glycemic Control Assessment Based on Consensus CGM Metrics*

Morten Mørup, Ali Mohebbi, Henrik Bengtsson, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

EEG Theta Power Is an Early Marker of Cognitive Decline in Dementia due to Alzheimer's Disease.

Morten Mørup, Gunhild Waldemar, Knut Engedal, 2018, Journal of Alzheimer's disease : JAD.

Regularity increases middle latency evoked and late induced beta brain response following proprioceptive stimulation

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2008, Brain Research.

Machine Learning-Based Adherence Detection of Type 2 Diabetes Patients on Once-Daily Basal Insulin Injections

Morten Mørup, Ali Mohebbi, Henrik Bengtsson, 2020, Journal of diabetes science and technology.

Whole brain functional connectivity predicted by indirect structural connections

Morten Mørup, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, 2017, 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Proprioceptive evoked gamma oscillations

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2007, Brain Research.

Reversible jump MCMC for Bayesian NMF

Morten Mørup, Mikkel N. Schmidt, 2010 .