Michael C. Thrun
Orcid: 0000-0001-9542-5543
According to our database1,
Michael C. Thrun
authored at least 23 papers
between 2017 and 2023.
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Bibliography
2023
Mach. Learn. Knowl. Extr., June, 2023
Informatica, 2023
2022
Künstliche Intell., 2022
Exploiting Distance-Based Structures in Data Using an Explainable AI for Stock Picking.
Inf., 2022
Proceedings of the Information Systems and Technologies, 2022
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
2021
Mach. Learn. Knowl. Extr., 2021
Correction to: Conventional displays of structures in data compared with interactive projection-based clustering (IPBC).
Int. J. Data Sci. Anal., 2021
Conventional displays of structures in data compared with interactive projection-based clustering (IPBC).
Int. J. Data Sci. Anal., 2021
Int. J. Comput. Intell. Appl., 2021
CoRR, 2021
Using Projection-Based Clustering to Find Distance- and Density-Based Clusters in High-Dimensional Data.
J. Classif., 2021
2020
Projection-Based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials.
IEEE Access, 2020
Improving the Sensitivity of Statistical Testing for Clusterability with Mirrored-Density Plots.
Proceedings of the 3rd Workshop on Machine Learning Methods in Visualisation for Big Data, 2020
Proceedings of the KI 2020: Advances in Artificial Intelligence, 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020
2019
Knowledge Discovery in Quarterly Financial Data of Stocks Based on the Prime Standard using a Hybrid of a Swarm with SOM.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019
2018
Projection-Based Clustering through Self-Organization and Swarm Intelligence, Combining Cluster Analysis with the Visualization of High-Dimensional Data.
Springer Vieweg, ISBN: 978-3-658-20539-3, 2018
2017
Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017