Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Scalable tensor factorizations for incomplete data
2010420 citationsEvrim Acar, Morten Mørup et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Morten Mørup's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Morten Mørup with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Morten Mørup more than expected).
This network shows the impact of papers produced by Morten Mørup. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Morten Mørup. The network helps show where Morten Mørup may publish in the future.
Co-authorship network of co-authors of Morten Mørup
This figure shows the co-authorship network connecting the top 25 collaborators of Morten Mørup.
A scholar is included among the top collaborators of Morten Mørup based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Morten Mørup. Morten Mørup is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Schmidt, Mikkel N., et al.. (2019). Analysis of Chromatographic Data using the Probabilistic PARAFAC2. neural information processing systems.2 indexed citations
Schmidt, Mikkel N., et al.. (2016). Completely random measures for modelling block-structured sparse networks. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 29. 4260–4268.18 indexed citations
Mørup, Morten, et al.. (2013). Modeling Temporal Evolution and Multiscale Structure in Networks. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 960–968.5 indexed citations
14.
Schmidt, Mikkel N. & Morten Mørup. (2010). Infinite non-negative matrix factorization. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 905–909.8 indexed citations
15.
Mørup, Morten, et al.. (2010). Infinite Relational Modeling of Functional Connectivity in Resting State fMRI. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 23. 1750–1758.17 indexed citations
16.
Mørup, Morten, Kristoffer H. Madsen, & Lars Kai Hansen. (2009). Latent Causal Modelling of Neuroimaging Data. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU).2 indexed citations
17.
Petersen, Michael Kai, Morten Mørup, & Lars Kai Hansen. (2009). Sparse but emotional decomposition of lyrics. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU).
18.
Mørup, Morten & Lars Kai Hansen. (2009). Sparse Coding and Automatic Relevance Determination for Multi-way models. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU).3 indexed citations
19.
Mørup, Morten & Lars Kai Hansen. (2009). Tuning pruning in sparse non-negative matrix factorization. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 1923–1927.19 indexed citations
20.
Mørup, Morten, Lars Kai Hansen, Josef Parnas, & Sidse Arnfred. (2006). Decomposing the time-frequency representation of EEG using non-negative matrix and multi-way factorization. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU).28 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.