| Scalable tensor factorizations for incomplete data E Acar, DM Dunlavy, TG Kolda, M Mørup Chemometrics and Intelligent Laboratory Systems 106 (1), 41-56, 2011 | 862 | 2011 |
| Applications of tensor (multiway array) factorizations and decompositions in data mining M Mørup Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1 (1 …, 2011 | 325 | 2011 |
| Parallel factor analysis as an exploratory tool for wavelet transformed event-related EEG M Mørup, LK Hansen, CS Herrmann, J Parnas, SM Arnfred NeuroImage 29 (3), 938-947, 2006 | 324 | 2006 |
| Archetypal analysis for machine learning and data mining M Mørup, LK Hansen Neurocomputing 80, 54-63, 2012 | 261 | 2012 |
| Defining a local arterial input function for perfusion MRI using independent component analysis F Calamante, M Mørup, LK Hansen Magnetic Resonance in Medicine: An Official Journal of the International …, 2004 | 223 | 2004 |
| Nonnegative matrix factor 2-D deconvolution for blind single channel source separation MN Schmidt, M Mørup International Conference on Independent Component Analysis and Signal …, 2006 | 217 | 2006 |
| Algorithms for sparse nonnegative Tucker decompositions M Mørup, LK Hansen, SM Arnfred Neural Computation 20 (8), 2112-2131, 2008 | 209 | 2008 |
| ERPWAVELAB: A toolbox for multi-channel analysis of time–frequency transformed event related potentials M Mørup, LK Hansen, SM Arnfred Journal of neuroscience methods 161 (2), 361-368, 2007 | 169 | 2007 |
| Automatic relevance determination for multi‐way models M Mørup, LK Hansen Journal of Chemometrics: A Journal of the Chemometrics Society 23 (7‐8), 352-363, 2009 | 164 | 2009 |
| EEG theta power is an early marker of cognitive decline in dementia due to Alzheimer’s disease CS Musaeus, K Engedal, P Høgh, V Jelic, M Mørup, M Naik, ... Journal of Alzheimer's Disease 64 (4), 1359-1371, 2018 | 156 | 2018 |
| Non-linear calibration models for near infrared spectroscopy W Ni, L Nørgaard, M Mørup Analytica chimica acta 813, 1-14, 2014 | 120 | 2014 |
| Shift-invariant multilinear decomposition of neuroimaging data M Mørup, LK Hansen, SM Arnfred, LH Lim, KH Madsen NeuroImage 42 (4), 1439-1450, 2008 | 117 | 2008 |
| Nonparametric Bayesian modeling of complex networks: An introduction MN Schmidt, M Morup IEEE Signal Processing Magazine 30 (3), 110-128, 2013 | 109 | 2013 |
| A deep learning approach to adherence detection for type 2 diabetics A Mohebbi, TB Aradóttir, AR Johansen, H Bengtsson, M Fraccaro, ... 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 85 | 2017 |
| Infinite multiple membership relational modeling for complex networks M Mørup, MN Schmidt, LK Hansen 2011 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2011 | 80 | 2011 |
| Bayesian community detection M Mørup, MN Schmidt Neural computation 24 (9), 2434-2456, 2012 | 78 | 2012 |
| Classification of independent components of EEG into multiple artifact classes L Frølich, TS Andersen, M Mørup Psychophysiology 52 (1), 32-45, 2015 | 72 | 2015 |
| Archetypal analysis of diverse Pseudomonas aeruginosatranscriptomes reveals adaptation in cystic fibrosis airways JC Thøgersen, M Mørup, S Damkiær, S Molin, L Jelsbak BMC bioinformatics 14, 1-15, 2013 | 71 | 2013 |
| Approximate L0 constrained non-negative matrix and tensor factorization M Morup, KH Madsen, LK Hansen 2008 IEEE International Symposium on Circuits and Systems (ISCAS), 1328-1331, 2008 | 71 | 2008 |
| Decomposing the time-frequency representation of EEG using non-negative matrix and multi-way factorization M Mørup, LK Hansen, J Parnas, SM Arnfred Technical University of Denmark Technical Report, 1-28, 2006 | 71 | 2006 |
Mikkel N. SchmidtTechnical University of DenmarkE-mail confirmado em dtu.dk
