Christian Merkwirth
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Artificial Intelligence top 10%
- Materials Chemistry
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Ulrich ParlitzThomas LengauerWerner LauterbornJoerg WichardMaciej OgorzałekDirk NeumannMartin StåhlHarald Mauser
- Topics
- Neural Networks and Applications (10 papers)Computational Drug Discovery Methods (6 papers)Neural Networks Stability and Synchronization (4 papers)
In The Last Decade
Christian Merkwirth
24 papers receiving 391 citations
Peers
Comparison fields: 5 of 104
- Computational Theory and Mathematics 142
- Molecular Biology 112
- Artificial Intelligence 112
- Materials Chemistry 45
- Statistical and Nonlinear Physics 41
Countries citing papers authored by Christian Merkwirth
This map shows the geographic impact of Christian Merkwirth'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 Christian Merkwirth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christian Merkwirth more than expected).
Fields of papers citing papers by Christian Merkwirth
This network shows the impact of papers produced by Christian Merkwirth. 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 Christian Merkwirth. The network helps show where Christian Merkwirth may publish in the future.
Co-authorship network of co-authors of Christian Merkwirth
This figure shows the co-authorship network connecting the top 25 collaborators of Christian Merkwirth. A scholar is included among the top collaborators of Christian Merkwirth 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 Christian Merkwirth. Christian Merkwirth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 2 | |
| 4 | Wavelet based classification of skin lesion images | 7 |
| 5 | 4 | |
| 6 | 28 | |
| 7 | 16 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 12 | |
| 12 | 13 | |
| 13 | Finite iteration DT-CNN - new design and operation principles | 5 |
| 14 | 4 | |
| 15 | 62 | |
| 16 | 1 | |
| 17 | Mathematical methods for forecasting bank transaction data | 9 |
| 18 | 1 | |
| 19 | 49 | |
| 20 | 80 |
About Christian Merkwirth
Christian Merkwirth is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Pharmaceutical Science, having authored 24 papers that have together received 414 indexed citations. Recurring topics across this work include Neural Networks and Applications (10 papers), Computational Drug Discovery Methods (6 papers) and Neural Networks Stability and Synchronization (4 papers). The work is most often cited by research in Computational Theory and Mathematics (142 citations), Pharmaceutical Science (32 citations) and Artificial Intelligence (112 citations). Christian Merkwirth has collaborated with scholars based in Germany, Poland and Austria. Frequent co-authors include Ulrich Parlitz, Thomas Lengauer, Werner Lauterborn, Joerg Wichard, Maciej Ogorzałek, Dirk Neumann, Martin Ståhl, Harald Mauser, Tanja Schulz‐Gasch and Olivier Roche. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Blood.
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.