Christin Schäfer
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Cognitive Neuroscience top 5%
- Signal Processing top 5%
- Molecular Biology
- Co-authors
- Sören SonnenburgGunnar RätschBernhard SchölkopfGabriel CurioS. LemmK. MüllerPavel LaskovIgor Kotenko
- Topics
- Network Security and Intrusion Detection (3 papers)Benford’s Law and Fraud Detection (3 papers)Anomaly Detection Techniques and Applications (3 papers)
In The Last Decade
Christin Schäfer
14 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 704
- Computer Vision and Pattern Recognition 614
- Cognitive Neuroscience 348
- Signal Processing 217
- Molecular Biology 160
Countries citing papers authored by Christin Schäfer
This map shows the geographic impact of Christin Schäfer'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 Christin Schäfer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christin Schäfer more than expected).
Fields of papers citing papers by Christin Schäfer
This network shows the impact of papers produced by Christin Schäfer. 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 Christin Schäfer. The network helps show where Christin Schäfer may publish in the future.
Co-authorship network of co-authors of Christin Schäfer
This figure shows the co-authorship network connecting the top 25 collaborators of Christin Schäfer. A scholar is included among the top collaborators of Christin Schäfer 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 Christin Schäfer. Christin Schäfer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 24 | |
| 3 | Large Scale Multiple Kernel Learningbreakdown → | 853 |
| 4 | 68 | |
| 5 | Data Driven Identification of Sources of Errors for Improving Survey Quality | 1 |
| 6 | 11 | |
| 7 | Automatic Identification of Faked and Fraudulent Interviews in the German SOEP | 12 |
| 8 | Visualization of anomaly detection using prediction sensitivity | 30 |
| 9 | A General and Efficient Multiple Kernel Learning Algorithm | 108 |
| 10 | 55 | |
| 11 | 156 | |
| 12 | Identification, Characteristics and Impact of Faked and Fraudulent Interviews in Surveys | 2 |
| 13 | 49 | |
| 14 | 166 | |
| 15 | 5 |
About Christin Schäfer
Christin Schäfer is a scholar working on Statistics and Probability, History and Philosophy of Science and Artificial Intelligence, having authored 15 papers that have together received 1.5k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (3 papers), Benford’s Law and Fraud Detection (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (614 citations), Artificial Intelligence (704 citations) and Signal Processing (217 citations). Christin Schäfer has collaborated with scholars based in Germany, Russia and France. Frequent co-authors include Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf, Gabriel Curio, S. Lemm, K. Müller, Pavel Laskov, Igor Kotenko, Benjamin Blankertz and Guido Dornhege. Their work appears in journals such as The Journal of Infectious Diseases, IEEE Transactions on Biomedical Engineering and BMC Bioinformatics.
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.