Martin Wistuba
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Economics and Econometrics top 10%
- Computer Vision and Pattern Recognition
- Management Science and Operations Research top 10%
- Co-authors
- Lars Schmidt-ThiemeNicolas SchillingJosif GrabockaMit ShahΑλέξανδρος ΝανόπουλοςAmbrish RawatMarco PlatznerHorst Samulowitz
- Topics
- Machine Learning and Data Classification (11 papers)Advanced Multi-Objective Optimization Algorithms (6 papers)Metaheuristic Optimization Algorithms Research (5 papers)
- Journals
- IEEE Transactions on Knowledge and Data EngineeringMachine LearningKnowledge and Information Systems
- Partner nations
- GermanyIrelandUnited States
In The Last Decade
Martin Wistuba
26 papers receiving 546 citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 370
- Signal Processing 309
- Economics and Econometrics 107
- Computer Vision and Pattern Recognition 55
- Management Science and Operations Research 51
Countries citing papers authored by Martin Wistuba
This map shows the geographic impact of Martin Wistuba'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 Martin Wistuba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Wistuba more than expected).
Fields of papers citing papers by Martin Wistuba
This network shows the impact of papers produced by Martin Wistuba. 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 Martin Wistuba. The network helps show where Martin Wistuba may publish in the future.
Co-authorship network of co-authors of Martin Wistuba
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Wistuba. A scholar is included among the top collaborators of Martin Wistuba 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 Martin Wistuba. Martin Wistuba is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 1 | |
| 3 | 11 | |
| 4 | 10 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | Bayesian Optimization Combined with Successive Halving for Neural Network Architecture Optimization. | 2 |
| 10 | Multi-Plant Photovoltaic Energy Forecasting Challenge with Regression Tree Ensembles and Hourly Average Forecasts. | 1 |
| 11 | Geo_ML @ MediaEval Placing Task 2015 | 1 |
| 12 | 13 | |
| 13 | 34 | |
| 14 | 49 | |
| 15 | 2 | |
| 16 | 9 | |
| 17 | Learning time-series shapeletsbreakdown → | 275 |
| 18 | Supervised Clustering of Social Media Streams. | 7 |
| 19 | 10 | |
| 20 | 7 |
About Martin Wistuba
Martin Wistuba is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Signal Processing, having authored 26 papers that have together received 561 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (11 papers), Advanced Multi-Objective Optimization Algorithms (6 papers) and Metaheuristic Optimization Algorithms Research (5 papers). The work is most often cited by research in Signal Processing (309 citations), Artificial Intelligence (370 citations) and Management Science and Operations Research (51 citations). Martin Wistuba has collaborated with scholars based in Germany, Ireland and United States. Frequent co-authors include Lars Schmidt-Thieme, Nicolas Schilling, Josif Grabocka, Mit Shah, Αλέξανδρος Νανόπουλος, Ambrish Rawat, Marco Platzner, Horst Samulowitz, Beat Buesser and Parikshit Ram. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Machine Learning and Knowledge and Information Systems.
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.