Bernhard Schoelkopf
- Artificial Intelligence top 5%
- Cognitive Neuroscience top 10%
- Computer Vision and Pattern Recognition top 10%
- Cellular and Molecular Neuroscience
- Signal Processing
- Co-authors
- Mingming GongKun ZhangSuzanne MartensMichael BenschFemke NijboerNiels BirbaumerAlireza GharabaghiSebastian Halder
- Topics
- Bayesian Modeling and Causal Inference (3 papers)Blind Source Separation Techniques (3 papers)Natural Language Processing Techniques (3 papers)
- Journals
- Clinical NeurophysiologyFrontiers in Human NeuroscienceANU Open Research (Australian National University)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Bernhard Schoelkopf
19 papers receiving 467 citations
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 237
- Cognitive Neuroscience 147
- Computer Vision and Pattern Recognition 90
- Cellular and Molecular Neuroscience 84
- Signal Processing 35
Countries citing papers authored by Bernhard Schoelkopf
This map shows the geographic impact of Bernhard Schoelkopf'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 Bernhard Schoelkopf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernhard Schoelkopf more than expected).
Fields of papers citing papers by Bernhard Schoelkopf
This network shows the impact of papers produced by Bernhard Schoelkopf. 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 Bernhard Schoelkopf. The network helps show where Bernhard Schoelkopf may publish in the future.
Co-authorship network of co-authors of Bernhard Schoelkopf
This figure shows the co-authorship network connecting the top 25 collaborators of Bernhard Schoelkopf. A scholar is included among the top collaborators of Bernhard Schoelkopf 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 Bernhard Schoelkopf. Bernhard Schoelkopf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 27 | |
| 2 | 2 | |
| 3 | 9 | |
| 4 | 11 | |
| 5 | 21 | |
| 6 | 15 | |
| 7 | 7 | |
| 8 | Discovering Temporal Causal Relations from Subsampled Data | 23 |
| 9 | 81 | |
| 10 | 10 | |
| 11 | Kernel Mean Estimation and Stein Effect | 10 |
| 12 | 7 | |
| 13 | 56 | |
| 14 | Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm. | 31 |
| 15 | Inverse Reinforcement Learning for Strategy Extraction | 2 |
| 16 | 11 | |
| 17 | 135 | |
| 18 | A kernel method to comparing distributions | 1 |
| 19 | Kernel Constrained Covariance for Dependence Measurement | 24 |
About Bernhard Schoelkopf
Bernhard Schoelkopf is a scholar working on Artificial Intelligence, Signal Processing and Statistics and Probability, having authored 19 papers that have together received 483 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Blind Source Separation Techniques (3 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Health Informatics (11 citations), Cognitive Neuroscience (147 citations) and Artificial Intelligence (237 citations). Bernhard Schoelkopf has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Mingming Gong, Kun Zhang, Suzanne Martens, Michael Bensch, Femke Nijboer, Niels Birbaumer, Alireza Gharabaghi, Sebastian Halder, J. Hill and Mrinmaya Sachan. Their work appears in journals such as Clinical Neurophysiology, Frontiers in Human Neuroscience and ANU Open Research (Australian National University).
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.