Philipp Thölke
Impact in
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- Computational Drug Discovery Methods
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- EEG and Brain-Computer Interfaces
Papers in
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- Protein Structure and Dynamics 2
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- EEG and Brain-Computer Interfaces 1
- Co-authors
- Gianni De Fabritiis (2 shared papers)Karim Jerbi (4 shared papers)Frank Noé (1 shared paper)Adrià Pérez (1 shared paper)Maciej Majewski (1 shared paper)Nicholas E. Charron (1 shared paper)Brooke E. Husic (1 shared paper)Stefan H. Doerr (1 shared paper)
- Journals
- Nature Communications (1 paper)Journal of Chemical Theory and Computation (1 paper)Neuroscience of Consciousness (1 paper)NeuroImage (1 paper)Communications Biology (1 paper)
- Partner nations
- CanadaUnited StatesItaly
In The Last Decade
Philipp Thölke
6 papers receiving 229 citations
Philipp Thölke's Hit Papers
Peers
Comparison fields: 5 of 102
- Computational Theory and Mathematics 33
- Cognitive Neuroscience 29
- Materials Chemistry 65
- Molecular Biology 62
- Artificial Intelligence 28
Countries citing papers authored by Philipp Thölke
This map shows the geographic impact of Philipp Thölke'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 Philipp Thölke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Thölke more than expected).
Fields of papers citing papers by Philipp Thölke
This network shows the impact of papers produced by Philipp Thölke. 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 Philipp Thölke. The network helps show where Philipp Thölke may publish in the future.
Co-authors
The 25 scholars most cited alongside Philipp Thölke, 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 | Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data Hit paper breakdown → | 2023 | 105 |
| 2 | 2023 | 69 | |
| 3 | 2024 | 37 | |
| 4 | 2024 | 16 | |
| 5 | 2025 | 2 | |
| 6 | 2025 | 2 |
About Philipp Thölke
Philipp Thölke is a scholar working on Molecular Biology, Cognitive Neuroscience, Electrical and Electronic Engineering, Materials Chemistry and Cardiology and Cardiovascular Medicine, having authored 6 papers that have together received 231 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (2 papers), Machine Learning in Materials Science (2 papers), Imbalanced Data Classification Techniques (1 paper), Electricity Theft Detection Techniques (1 paper), Blind Source Separation Techniques (1 paper), EEG and Brain-Computer Interfaces (1 paper), Enzyme Structure and Function (1 paper) and Sleep and related disorders (1 paper). The work is most often cited by research in Computational Theory and Mathematics (33 citations), Cognitive Neuroscience (29 citations), Materials Chemistry (65 citations), Molecular Biology (62 citations) and Artificial Intelligence (28 citations). Philipp Thölke has collaborated with scholars based in Canada, United States and Italy. Frequent co-authors include Gianni De Fabritiis, Karim Jerbi, Frank Noé, Adrià Pérez, Maciej Majewski, Nicholas E. Charron, Brooke E. Husic, Stefan H. Doerr, Toni Giorgino and Cecilia Clementi. Their work appears in journals such as Nature Communications, Journal of Chemical Theory and Computation, Neuroscience of Consciousness, NeuroImage and Communications Biology.
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.