Janek Thomas
Impact in
- Artificial Intelligence top 5%
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Explainable Artificial Intelligence (XAI)
- Anomaly Detection Techniques and Applications
- Statistics and Probability top 5%
- Statistical Methods and Inference
Papers in ⓘ
-
- Machine Learning and Data Classification 8
- Data Stream Mining Techniques 2
- Machine Learning and Algorithms 2
- Metaheuristic Optimization Algorithms Research 2
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- Advanced Multi-Objective Optimization Algorithms 6
- Co-authors
- Bernd Bischl (12 shared papers)Jakob Richter (2 shared papers)Michel Lang (2 shared papers)Tobias Pielok (2 shared papers)Martin Binder (2 shared papers)Stefan Coors (2 shared papers)Marc Becker (1 shared paper)Anne‐Laure Boulesteix (1 shared paper)
- Journals
- Statistics and Computing (1 paper)Big Data (1 paper)Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (1 paper)IEEE Access (1 paper)Computational and Mathematical Methods in Medicine (1 paper)
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
Janek Thomas
15 papers receiving 586 citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Artificial Intelligence 205
- Statistics and Probability 50
- Health Informatics 7
- Health Information Management 20
- Environmental Engineering 39
Countries citing papers authored by Janek Thomas
This map shows the geographic impact of Janek Thomas'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 Janek Thomas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janek Thomas more than expected).
Fields of papers citing papers by Janek Thomas
This network shows the impact of papers produced by Janek Thomas. 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 Janek Thomas. The network helps show where Janek Thomas may publish in the future.
Co-authors
The 25 scholars most cited alongside Janek Thomas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges Hit paper breakdown → | 2023 | 398 |
| 2 | 2022 | 63 | |
| 3 | 2017 | 47 | |
| 4 | 2023 | 36 | |
| 5 | 2017 | 22 | |
| 6 | 2016 | 12 | |
| 7 | 2022 | 7 | |
| 8 | 2021 | 5 | |
| 9 | 2023 | 4 | |
| 10 | 2021 | 3 | |
| 11 | 2019 | 3 | |
| 12 | Meta learning for defaults: symbolic defaults | 2018 | 2 |
| 13 | 2022 | 2 | |
| 14 | 2018 | 1 | |
| 15 | Boosting Methods for 'GAMLSS' [R package gamboostLSS version 2.0-5] | 2021 | 1 |
About Janek Thomas
Janek Thomas is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Computer Vision and Pattern Recognition and Signal Processing, having authored 15 papers that have together received 606 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (8 papers), Advanced Multi-Objective Optimization Algorithms (6 papers), Data Stream Mining Techniques (2 papers), Time Series Analysis and Forecasting (2 papers), Software Engineering Research (2 papers), Machine Learning and Algorithms (2 papers), Metaheuristic Optimization Algorithms Research (2 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Artificial Intelligence (205 citations), Statistics and Probability (50 citations), Health Informatics (7 citations), Health Information Management (20 citations) and Environmental Engineering (39 citations). Janek Thomas has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Bernd Bischl, Jakob Richter, Michel Lang, Tobias Pielok, Martin Binder, Stefan Coors, Marc Becker, Anne‐Laure Boulesteix, Theresa Ullmann and Difan Deng. Their work appears in journals such as Statistics and Computing, Big Data, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, IEEE Access and Computational and Mathematical Methods in Medicine.
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.