| Overt attention in natural scenes: Objects dominate features J Stoll, M Thrun, A Nuthmann, W Einhäuser Vision research 107, 36-48, 2015 | 83 | 2015 |
| Projection-based clustering through self-organization and swarm intelligence: combining cluster analysis with the visualization of high-dimensional data MC Thrun Springer, 2018 | 62 | 2018 |
| Swarm intelligence for self-organized clustering MC Thrun, A Ultsch Artificial Intelligence 290, 103237, 2021 | 51 | 2021 |
| Analyzing the fine structure of distributions MC Thrun, T Gehlert, A Ultsch PloS one 15 (10), e0238835, 2020 | 44 | 2020 |
| Identification of molecular fingerprints in human heat pain thresholds by use of an interactive mixture model R toolbox (AdaptGauss) A Ultsch, MC Thrun, O Hansen-Goos, J Lötsch International journal of molecular sciences 16 (10), 25897-25911, 2015 | 42 | 2015 |
| Visualization and 3D printing of multivariate data of biomarkers MC Thrun, F Lerch Václav Skala-UNION Agency, 2016 | 40 | 2016 |
| Clustering benchmark datasets exploiting the fundamental clustering problems MC Thrun, A Ultsch Data in brief 30, 105501, 2020 | 34 | 2020 |
| Using Projection-Based Clustering to Find Distanceand Density-Based Clusters in High-Dimensional Data MC Thrun, A Ultsch Journal of Classification 38 (2), 280–312, 2021 | 33 | 2021 |
| Knowledge discovery from high-frequency stream nitrate concentrations: hydrology and biology contributions AH Aubert, MC Thrun, L Breuer, A Ultsch Scientific reports 6 (1), 1-8, 2016 | 26 | 2016 |
| Machine-learned data structures of lipid marker serum concentrations in multiple sclerosis patients differ from those in healthy subjects J Lötsch, M Thrun, F Lerch, R Brunkhorst, S Schiffmann, D Thomas, ... International journal of molecular sciences 18 (6), 1217, 2017 | 22 | 2017 |
| Credible Visualizations for Planar Projections A Ultsch, MC Thrun Proc. Workshop on Self-Organizing Maps (WSOM), 256-260, 2017 | 20 | 2017 |
| Fundamental clustering algorithms suite MC Thrun, Q Stier SoftwareX 13 (C), 100642, 2021 | 18 | 2021 |
| Determination of CD43 and CD200 surface expression improves accuracy of B‐cell lymphoma immunophenotyping J Hoffmann, M Rother, U Kaiser, MC Thrun, C Wilhelm, A Gruen, ... Cytometry Part B: Clinical Cytometry 98 (6), 476-482, 2020 | 16 | 2020 |
| Machine-learned analysis of the association of next-generation sequencing–based human TRPV1 and TRPA1 genotypes with the sensitivity to heat stimuli and topically applied capsaicin D Kringel, G Geisslinger, E Resch, BG Oertel, MC Thrun, S Heinemann, ... Pain 159 (7), 1366, 2018 | 16 | 2018 |
| Distance-Based Clustering Challenges for Unbiased Benchmarking Studies MC Thrun Scientific Reports 11 (1), 18988, 2021 | 15 | 2021 |
| Explainable AI Framework for Multivariate Hydrochemical Time Series M Thrun, A Ultsch, L Breuer Mach. Learn. Knowl. Extr. 3 (1), 170-205, 2021 | 14 | 2021 |
| Uncovering High-Dimensional Structures of Projections from Dimensionality Reduction Methods MC Thrun, A Ultsch MethodsX, 101093, 2020 | 13 | 2020 |
| Interactive machine learning tool for clustering in visual analytics M Thrun, F Pape, A Ultsch 2020 IEEE 7th International Conference on Data Science and Advanced …, 2020 | 10 | 2020 |
| Rapid serial processing of natural scenes: color modulates detection but neither recognition nor the attentional blink S Marx, O Hansen-Goos, M Thrun, W Einhäuser Journal of Vision 14 (14), 4-4, 2014 | 9 | 2014 |
| The Exploitation of Distance Distributions for Clustering MC Thrun International Journal of Computational Intelligence and Applications, 2150016, 2021 | 8 | 2021 |
Alfred UltschProfessur Datenbionik, University of MarburgVerified email at mabi.de
