Felix Mohr
- Artificial Intelligence top 10%
- Machine Learning and Data Classification 14
- Advanced Software Engineering Methodologies 8
- Machine Learning and Algorithms 7
- Data Stream Mining Techniques 2
- Information Systems top 10%
- Service-Oriented Architecture and Web Services 11
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- Software System Performance and Reliability 6
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- Business Process Modeling and Analysis 2
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- Advanced Neural Network Applications 2
- Co-authors
- Marcel WeverEyke HüllermeierJan N. van RijnMartin DienwiebelPantcho StoyanovHolger H. HoosMarkus W. HollmannHans Kleine Büning
- Journals
- Environmental Science & Technology (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)Critical Care Medicine (1 paper)
- Partner nations
- GermanyColombiaNetherlands
In The Last Decade
Felix Mohr
30 papers receiving 365 citations
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 188
- Developmental Neuroscience 15
- Health Information Management 13
- Information Systems 61
- Software 10
Countries citing papers authored by Felix Mohr
This map shows the geographic impact of Felix Mohr'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 Felix Mohr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felix Mohr more than expected).
Fields of papers citing papers by Felix Mohr
This network shows the impact of papers produced by Felix Mohr. 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 Felix Mohr. The network helps show where Felix Mohr may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Felix Mohr, 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 | 2024 | 1 | |
| 2 | 2024 | 8 | |
| 3 | 2023 | 23 | |
| 4 | 2023 | 22 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 9 | |
| 7 | Replacing the Ex-Def Baseline in AutoML by Naive AutoML | 2021 | 2 |
| 8 | 2021 | 1 | |
| 9 | 2021 | 53 | |
| 10 | 2019 | 26 | |
| 11 | ML-Plan for Unlimited-Length Machine Learning Pipelines | 2018 | 7 |
| 12 | 2018 | 6 | |
| 13 | Programmatic Task Network Planning | 2018 | 3 |
| 14 | 2018 | 3 | |
| 15 | Automated Software and Service Composition: A Survey and Evaluating Review | 2016 | 3 |
| 16 | 2016 | 4 | |
| 17 | 2015 | 6 | |
| 18 | 2014 | 3 | |
| 19 | 2013 | 32 | |
| 20 | 2013 | 0 |
About Felix Mohr
Felix Mohr is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications, having authored 31 papers that have together received 386 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (14 papers), Service-Oriented Architecture and Web Services (11 papers), Advanced Software Engineering Methodologies (8 papers), Machine Learning and Algorithms (7 papers), Software System Performance and Reliability (6 papers), Business Process Modeling and Analysis (2 papers), Advanced Neural Network Applications (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (188 citations), Developmental Neuroscience (15 citations) and Health Information Management (13 citations). Felix Mohr has collaborated with scholars based in Germany, Colombia and Netherlands. Frequent co-authors include Marcel Wever, Eyke Hüllermeier, Jan N. van Rijn, Martin Dienwiebel, Pantcho Stoyanov, Holger H. Hoos, Markus W. Hollmann, Hans Kleine Büning, Albert Wong and Emiel Rorije. Their work appears in journals such as Environmental Science & Technology, IEEE Transactions on Pattern Analysis and Machine Intelligence and Critical Care 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.