André Biedenkapp
- Artificial Intelligence
- Computational Theory and Mathematics
- Control and Systems Engineering
- Information Systems
- Industrial and Manufacturing Engineering
- Co-authors
- Frank HutterMarius LindauerYingjie MiaoVu NguyenRoberto CalandraBaohe ZhangAleksandra FaustJack Parker-Holder
- Topics
- Evolutionary Algorithms and Applications (4 papers)Machine Learning and Data Classification (4 papers)Metaheuristic Optimization Algorithms Research (3 papers)
- Journals
- Journal of Artificial Intelligence ResearcharXiv (Cornell University)International Conference on Artificial Intelligence and Statistics
- Partner nations
- GermanyIndiaUnited Kingdom
In The Last Decade
André Biedenkapp
6 papers receiving 87 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 67
- Computational Theory and Mathematics 24
- Control and Systems Engineering 11
- Information Systems 8
- Industrial and Manufacturing Engineering 8
Countries citing papers authored by André Biedenkapp
This map shows the geographic impact of André Biedenkapp'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 André Biedenkapp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites André Biedenkapp more than expected).
Fields of papers citing papers by André Biedenkapp
This network shows the impact of papers produced by André Biedenkapp. 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 André Biedenkapp. The network helps show where André Biedenkapp may publish in the future.
Co-authorship network of co-authors of André Biedenkapp
This figure shows the co-authorship network connecting the top 25 collaborators of André Biedenkapp. A scholar is included among the top collaborators of André Biedenkapp 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 André Biedenkapp. André Biedenkapp 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 | 48 | |
| 3 | 3 | |
| 4 | 15 | |
| 5 | On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning | 3 |
| 6 | 2 | |
| 7 | 19 |
About André Biedenkapp
André Biedenkapp is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Infectious Diseases, having authored 7 papers that have together received 90 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (4 papers), Machine Learning and Data Classification (4 papers) and Metaheuristic Optimization Algorithms Research (3 papers). The work is most often cited by research in Artificial Intelligence (67 citations), Computational Theory and Mathematics (24 citations) and Health Informatics (2 citations). André Biedenkapp has collaborated with scholars based in Germany, India and United Kingdom. Frequent co-authors include Frank Hutter, Marius Lindauer, Yingjie Miao, Vu Nguyen, Roberto Calandra, Baohe Zhang, Aleksandra Faust, Jack Parker-Holder, Xingyou Song and Holger H. Hoos. Their work appears in journals such as Journal of Artificial Intelligence Research, arXiv (Cornell University) and International Conference on Artificial Intelligence and Statistics.
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.