Karl Kumbier
- Artificial Intelligence top 0.5%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Molecular Biology
- Co-authors
- Bin YuChandan SinghWilliam J. MurdochReza Abbasi-AslJames B. BrownSumanta BasuMarilou P. Sison-MangusMichelle Newcomer
- Topics
- Machine Learning and Data Classification (3 papers)Explainable Artificial Intelligence (XAI) (2 papers)Parkinson's Disease Mechanisms and Treatments (2 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Karl Kumbier
11 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 190
- Artificial Intelligence 1.9k
- Computer Networks and Communications 268
- Computer Vision and Pattern Recognition 249
- Electrical and Electronic Engineering 240
- Molecular Biology 218
Countries citing papers authored by Karl Kumbier
This map shows the geographic impact of Karl Kumbier'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 Karl Kumbier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karl Kumbier more than expected).
Fields of papers citing papers by Karl Kumbier
This network shows the impact of papers produced by Karl Kumbier. 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 Karl Kumbier. The network helps show where Karl Kumbier may publish in the future.
Co-authorship network of co-authors of Karl Kumbier
This figure shows the co-authorship network connecting the top 25 collaborators of Karl Kumbier. A scholar is included among the top collaborators of Karl Kumbier 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 Karl Kumbier. Karl Kumbier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 9 | |
| 6 | 3 | |
| 7 | 17 | |
| 8 | 79 | |
| 9 | A Debiased MDI Feature Importance Measure for Random Forests | 3 |
| 10 | Domain-inspired machine learning for hypothesis extraction in biological data | 2 |
| 11 | Definitions, methods, and applications in interpretable machine learningbreakdown → | 1251 |
| 12 | 191 | |
| 13 | Artificial intelligence and statisticsbreakdown → | 1577 |
About Karl Kumbier
Karl Kumbier is a scholar working on General Social Sciences, Biophysics and Artificial Intelligence, having authored 13 papers that have together received 3.1k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (3 papers), Explainable Artificial Intelligence (XAI) (2 papers) and Parkinson's Disease Mechanisms and Treatments (2 papers). The work is most often cited by research in Health Informatics (152 citations), Artificial Intelligence (1.9k citations) and Computer Science Applications (107 citations). Karl Kumbier has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Bin Yu, Bin Yu, Chandan Singh, William J. Murdoch, Reza Abbasi-Asl, James B. Brown, Sumanta Basu, Bin Yu, Marilou P. Sison-Mangus and Michelle Newcomer. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.
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.