Peer reviewed journal articles

• Kristoffer J Albers, Karen S Ambrosen, Matthew G Liptrot, Tim B Dyrby, Mikkel N Schmidt, Morten Mørup, “Using connectomics for predictive assessment of brain parcellations”, NeuroImage(2021)
• Karen S. Ambrosen, Simon F. Eskildsen, Max Hinne, Kristine Krug, Henrik Lundell, Mikkel N .Schmidt, Marcel A. J .van Gerven, Morten Mørup, Tim B. Dyrby, “Validation of structural brain connectivity networks: The impact of scanning parameters”, NeuroImage(2020)
• Søren F.V. Nielsen, Mikkel N. Schmidt, Kristoffer H. Madsen, Morten Mørup. “Predictive assessment of models for dynamic functional connectivity”, NeuroImage (2017)
• Rasmus E. Røge, Kristoffer H. Madsen, Mikkel N. Schmidt, Morten Mørup. “Infinite von Mises–Fisher Mixture Modeling of Whole Brain fMRI Data”, Neural Computation (2017)
• Max Hinne , Annet Meijers, Rembrandt Bakker, Paul H. E. Tiesinga, Morten Mørup, Marcel A. J. van Gerven. “The missing link: Predicting connectomes from noisy and partially observed tract tracing data. Plos One Computational Biology (2017)
• Kristoffer H. Madsen, Nathan W.Churchill, and Morten Mørup. “Quantifying functional connectivity in multi-subject fMRI data using component models” Human Brain Mapping (2016).
• Nathan W.Churchill, Kristoffer H. Madsen, and Morten Mørup. “The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI.” Neural Computation (2016).
• Jesper L. Hinrich; Sophia Bardenfleth; Rasmus Røge; Nathan Churchill; Kristoffer H. Madsen; Morten Mørup, “Archetypal Analysis for Modeling Multi-Subject fMRI Data,” in IEEE Journal of Selected Topics in Signal Processing , vol.PP, no.99, pp.1-1
  doi: 10.1109/JSTSP.2016.2595103
• Tue Herlau, Mikkel N. Schmidt, Morten Mørup, “Infinite-Degree-Corrected Stochastic Block Model”, Physical Review E, vol. 90(3), 032819, 2014.
• Kasper Winther Andersen, Kristoffer H. Madsen, Hartwig Roman Siebner, Mikkel N. Schmidt, Morten Mørup, Lars Kai Hansen, “Non-parametric Bayesian graph models reveal community structure in resting state fMRI”, NeuroImage, 2014.
• M. N. Schmidt, M. Mørup, “Non-parametric Bayesian modeling of complex networks. An introduction”, IEEE Signal Processing Magazine, vol. 30(3), pp. 110-128, 2013.

Peer reviewed conference articles

• R. Røge, K. S. Ambrosen, K. J. Albers, C. T. Eriksen, M. G. Liptrot, M. N. Schmidt, K. H. Madsen, M. Mørup, “Whole Brain Functional Connectivity Predicted by Indirect Structural Connection”, PRNI 2017.
• Søren F.V. Nielsen, Kristoffer H. Madsen, Mikkel N. Schmidt, Morten Mørup. “Modeling Dynamic Functional Connectivity using a Wishart Mixture Model”, PRNI 2017.
• J. L. Hinrich, S. F. V. Nielsen, N. A. B. Riis, C. T. Eriksen, J. Frøsig, M. D. F. Kristensen, M. N. Schmidt, K. H. Madsen, M. Mørup, “Scalable group level probabilistic sparse factor analysis”, ICASSP 2017.
• Tue Herlau, Mikkel N. Schmidt, Morten Mørup, Completely random measures for modelling block-structured sparse networks, NIPS 2016.
• Kristoffer J. Albers, Morten Mørup, Mikkel N. Schmidt, The influence of hyper-parameters in the infinite relational model, Machine Learning for Signal Processing (MLSP), 2016 IEEE 26th International Workshop on.
• Philip H. Jørgensen, Morten Mørup, Mikkel N. Schmidt, T. Herlau, Bayesian latent feature modeling for modeling bipartite networks with overlapping groups, Machine Learning for Signal Processing (MLSP), 2016 IEEE 26th International Workshop on.
• Jesper L. Hinrich, Søren F. V. Nielsen, Kristoffer H. Madsen and M. Mørup, “Variational group-PCA for intrinsic dimensionality determination in fMRI data,” 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI), Trento, Italy, 2016, pp. 1-4.
  
• Søren Føns Vind Nielsen, Kristoffer H. Madsen, Rasmus Røge, Mikkel N. Schmidt, Morten Mørup, Nonparametric modeling of dynamic functional connectivity in fmri data, Proceedings of the 5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI 2015), 2015.
• Rasmus Røge, Kristoffer H. Madsen, Mikkel N. Schmidt, Morten Mørup, Unsupervised segmentation of task activated regions in fmRI. Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015
• Mikkel N. Schmidt, Kristoffer J. Albers, Numerical approximations for speeding up MCMC inference in the infinite relational model. Signal Processing Conference (EUSIPCO), 2015 23rd European
• Søren Føns Vind Nielsen, Morten Mørup, Non-negative Tensor Factorization with Missing Data for the Modeling of Gene Expressions in the Human Brain. IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, 2014.
• Mikkel N. Schmidt, Tue Herlau, Morten Mørup, Discovering Hierarchical Structure In Normal Relational Data. 4th International Workshop on Cognitive Information Processing, 2014.
• Karen S. Ambrosen, Kristoffer J. Albers, Tim Dyrby, Mikkel N. Schmidt and Morten Mørup. Nonparametric Bayesian Clustering of Structural Whole Brain Connectivity in Full Image Resolution. 4th International Workshop on Pattern Recognition in NeuroImaging (PRNI2014), 2014
• Karen S. Ambrosen, Tue Herlau, Tim Dyrby, Mikkel N. Schmidt and Morten Mørup. Comparing Structural Brain Connectivity by the Infinite Relational Model. 3rd International Workshop on Pattern Recognition in NeuroImaging (PRNI2013), 2013

• Kristoffer Jon Albers, Andreas Leon Aagard Moth, Morten Mørup, Mikkel N. Schmidt, Large Scale Inference in the Infinite Relational Model: Gibbs Sampling is not Enough.

   IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, 2013

Peer reviewed abstracts

• Josefine Korzen, Kristoffer H. Madsen, Morten Mørup, Quantifying Temporal States in rsfMRI Data using Bayesian Nonparametrics. Organization for Human Brain Mapping 2014. Click here to see poster.
• Kasper W. Andersen, Kristoffer H. Madsen, Hartwig Roman Siebner, Mikkel N. Schmidt, Morten Mørup, Lars Kai Hansen, Community structure in resting state complex networks. Organization for Human Brain Mapping 2014

In the media

• Forskere vil lave ‘Google Street View’ i hjernen, Videnskab.dk, 25. juni 2013
• Fremtidens hjerneatlas, Videnskabens Verden 25. juni 2013 kl. 14:03 på P1