Credible visualizations for planar projections. - Alfred Ultsch; Michael C. Thrun (WSOM, 2017)

Projection-Based Clustering through Self-Organization and Swarm Intelligence, Combining Cluster Analysis with the Visualization of High-Dimensional Data. - Michael C. Thrun (Springer Vieweg, 2018)

Knowledge Discovery in Quarterly Financial Data of Stocks Based on the Prime Standard using a Hybrid of a Swarm with SOM. - Michael C. Thrun (ESANN, 2019)

Analyzing the Fine Structure of Distributions. - Michael C. Thrun; Tino Gehlert; Alfred Ultsch (CoRR, 2019)

Interactive Machine Learning Tool for Clustering in Visual Analytics. - Michael C. Thrun; Felix Pape; Alfred Ultsch (DSAA, 2020)

Swarm Intelligence for Self-Organized Clustering (Extended Abstract). - Michael C. Thrun; Alfred Ultsch (IJCAI, 2020)

Swarm-Based Cluster Analysis for Knowledge Discovery. - Michael C. Thrun; Alfred Ultsch (KI, 2020)

Improving the Sensitivity of Statistical Testing for Clusterability with Mirrored-Density Plots. - Michael C. Thrun (MLVis@Eurographics/EuroVis, 2020)

Projection-Based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials. - Pedro A. López-García; Denisse L. Argote; Michael C. Thrun (IEEE Access, 2020)

Swarm intelligence for self-organized clustering. - Michael C. Thrun; Alfred Ultsch (Artif. Intell., 2021)

Using Projection-Based Clustering to Find Distance- and Density-Based Clusters in High-Dimensional Data. - Michael C. Thrun; Alfred Ultsch (J. Classif., 2021)

An Explainable AI System for the Diagnosis of High Dimensional Biomedical Data. - Alfred Ultsch; Jörg Hoffmann; Maximilian Röhnert; Malte Von Bonin; Uta Oelschlägel; Cornelia Brendel; Michael C. Thrun (CoRR, 2021)

The Exploitation of Distance Distributions for Clustering. - Michael C. Thrun (Int. J. Comput. Intell. Appl., 2021)

Conventional displays of structures in data compared with interactive projection-based clustering (IPBC). - Michael C. Thrun; Felix Pape; Alfred Ultsch (Int. J. Data Sci. Anal., 2021)

Correction to: Conventional displays of structures in data compared with interactive projection-based clustering (IPBC). - Michael C. Thrun; Felix Pape; Alfred Ultsch (Int. J. Data Sci. Anal., 2021)

Explainable AI Framework for Multivariate Hydrochemical Time Series. - Michael C. Thrun; Alfred Ultsch; Lutz Breuer (Mach. Learn. Knowl. Extr., 2021)

Fundamental clustering algorithms suite. - Michael C. Thrun; Quirin Stier (SoftwareX, 2021)

Interactive Toolbox for Two-Dimensional Gaussian Mixture Modeling. - Michael C. Thrun; Quirin Stier; Alfred Ultsch (ECML/PKDD (6), 2022)

Knowledge-Based Identification of Homogenous Structures in Gene Sets. - Michael C. Thrun (WorldCIST (1), 2022)

Exploiting Distance-Based Structures in Data Using an Explainable AI for Stock Picking. - Michael C. Thrun (Inf., 2022)

Identification of Explainable Structures in Data with a Human-in-the-Loop. - Michael C. Thrun (Künstliche Intell., 2022)

Deriving Homogeneous Subsets from Gene Sets by Exploiting the Gene Ontology. - Quirin Stier; Michael C. Thrun (Informatica, 2023)

Analyzing Quality Measurements for Dimensionality Reduction. - Michael C. Thrun; Julian Märte; Quirin Stier (Mach. Learn. Knowl. Extr., 2023)