Marcel Wever

629 citations
32 papers · 357 · h-index 9

Impact in

    • Machine Learning and Data Classification
    • Machine Learning and Algorithms
    • Data Stream Mining Techniques
    • Text and Document Classification Technologies
    • Imbalanced Data Classification Techniques
    • Anomaly Detection Techniques and Applications
    • Metaheuristic Optimization Algorithms Research

Papers in

    • Machine Learning and Data Classification 20
    • Machine Learning and Algorithms 15
    • Imbalanced Data Classification Techniques 4
    • Text and Document Classification Technologies 4
    • Evolutionary Algorithms and Applications 3
    • Data Stream Mining Techniques 3

Marcel Wever

28 papers receiving 336 citations

Peers

Marcel Wever
Comparison fields: 5 of 68
  • Artificial Intelligence 242
  • Software 15
  • Health Information Management 12
  • Management Science and Operations Research 29
  • Computer Science Applications 10
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Citations per year

Countries citing papers authored by Marcel Wever

Since Specialization
Citations

This map shows the geographic impact of Marcel Wever'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 Marcel Wever with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcel Wever more than expected).

Fields of papers citing papers by Marcel Wever

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcel Wever. 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 Marcel Wever. The network helps show where Marcel Wever may publish in the future.

Co-authors

The 21 scholars most cited alongside Marcel Wever, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marcel Wever Line = papers co-authored together Marcel Wever links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018113
2 202159
3 202133
4 202328
5 202016
6 202212
7 202112
8 202211
9
ML-Plan for Unlimited-Length Machine Learning Pipelines
201811
10
Automating Multi-Label Classification Extending ML-Plan
20197
11 20186
12 20186
13 20205
14 20184
15 20204
16 20204
17 20233
18 20243
19 20253
20 20173

About Marcel Wever

Marcel Wever is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Information Systems and Management and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 357 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (20 papers), Machine Learning and Algorithms (15 papers), Imbalanced Data Classification Techniques (4 papers), Text and Document Classification Technologies (4 papers), Evolutionary Algorithms and Applications (3 papers), Data Stream Mining Techniques (3 papers), Scientific Computing and Data Management (3 papers) and Software System Performance and Reliability (2 papers). The work is most often cited by research in Artificial Intelligence (242 citations), Software (15 citations), Health Information Management (12 citations), Management Science and Operations Research (29 citations) and Computer Science Applications (10 citations). Marcel Wever has collaborated with scholars based in Germany, Colombia and Belgium. Frequent co-authors include Eyke Hüllermeier, Felix Mohr, Bernard De Baets, Stefan Werner, Heiko Hamann, Willem Waegeman, David Schubert, Lennart Purucker, Jan N. van Rijn and Sebastian Fischer. Their work appears in journals such as Machine Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, Evolutionary Computation, Information Sciences and Journal of Artificial Intelligence Research.

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.

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