Bernhard Schoelkopf
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function 2
- Artificial Intelligence top 5%
- Bayesian Modeling and Causal Inference 3
- Natural Language Processing Techniques 3
- Explainable Artificial Intelligence (XAI) 2
- Adversarial Robustness in Machine Learning 2
- Human-Computer Interaction top 10%
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- Neuroscience and Neural Engineering 2
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- Blind Source Separation Techniques 3
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- Spectroscopy and Chemometric Analyses 2
- Co-authors
- Mingming GongKun ZhangSuzanne MartensMichael BenschFemke NijboerNiels BirbaumerAlireza GharabaghiSebastian Halder
- Journals
- Clinical Neurophysiology (1 paper)Frontiers in Human Neuroscience (1 paper)ANU Open Research (Australian National University) (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Bernhard Schoelkopf
19 papers receiving 467 citations
Peers
Comparison fields: 5 of 86
- Health Informatics 11
- Cognitive Neuroscience 147
- Artificial Intelligence 237
- Human-Computer Interaction 31
- Cellular and Molecular Neuroscience 84
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
The 25 scholars most cited alongside Bernhard Schoelkopf, 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 | 2023 | 27 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 9 | |
| 4 | 2022 | 11 | |
| 5 | 2022 | 21 | |
| 6 | 2021 | 15 | |
| 7 | 2021 | 7 | |
| 8 | Discovering Temporal Causal Relations from Subsampled Data | 2015 | 23 |
| 9 | 2015 | 81 | |
| 10 | 2015 | 10 | |
| 11 | Kernel Mean Estimation and Stein Effect | 2014 | 10 |
| 12 | 2014 | 7 | |
| 13 | 2014 | 56 | |
| 14 | Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm. | 2014 | 31 |
| 15 | Inverse Reinforcement Learning for Strategy Extraction | 2013 | 2 |
| 16 | 2013 | 11 | |
| 17 | 2010 | 135 | |
| 18 | A kernel method to comparing distributions | 2007 | 1 |
| 19 | Kernel Constrained Covariance for Dependence Measurement | 2005 | 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), Natural Language Processing Techniques (3 papers), Neural dynamics and brain function (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Adversarial Robustness in Machine Learning (2 papers), Spectroscopy and Chemometric Analyses (2 papers) and Neuroscience and Neural Engineering (2 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.