Andrei Belitski
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function 5
- Functional Brain Connectivity Studies 3
- EEG and Brain-Computer Interfaces 3
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- Neuroscience and Neural Engineering 2
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- Imbalanced Data Classification Techniques 1
- Neural Networks and Applications 1
- Machine Learning and Algorithms 1
- Machine Learning and Data Classification 1
- Co-authors
- Nikos K. LogothetisStefano PanzeriCesare MagriYusuke MurayamaArthur GrettonMarcelo A. MontemurroPeter DesainJason Farquhar
- Journals
- Journal of Neural Engineering (1 paper)Journal of Computational Neuroscience (1 paper)Journal of Neuroscience (1 paper)
- Partner nations
- GermanyItalyUnited Kingdom
In The Last Decade
Andrei Belitski
7 papers receiving 485 citations
Peers
Comparison fields: 5 of 53
- Cognitive Neuroscience 439
- Cellular and Molecular Neuroscience 214
- Human-Computer Interaction 21
- Signal Processing 34
- Sensory Systems 13
Countries citing papers authored by Andrei Belitski
This map shows the geographic impact of Andrei Belitski'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 Andrei Belitski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrei Belitski more than expected).
Fields of papers citing papers by Andrei Belitski
This network shows the impact of papers produced by Andrei Belitski. 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 Andrei Belitski. The network helps show where Andrei Belitski may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Andrei Belitski, 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 | 2011 | 79 | |
| 2 | 2010 | 64 | |
| 3 | 2008 | 303 | |
| 4 | 2006 | 11 | |
| 5 | Kernel Constrained Covariance for Dependence Measurement | 2005 | 24 |
| 6 | Sparse Greedy Minimax Probability Machine Classification | 2003 | 7 |
| 7 | Sparse Greedy Minimax Probability Machine Classification ; CU-CS-956-03 | 2003 | 1 |
About Andrei Belitski
Andrei Belitski is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 7 papers that have together received 489 indexed citations. Recurring topics across this work include Neural dynamics and brain function (5 papers), Functional Brain Connectivity Studies (3 papers), EEG and Brain-Computer Interfaces (3 papers), Neuroscience and Neural Engineering (2 papers), Imbalanced Data Classification Techniques (1 paper), Neural Networks and Applications (1 paper), Machine Learning and Algorithms (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Cognitive Neuroscience (439 citations), Cellular and Molecular Neuroscience (214 citations) and Human-Computer Interaction (21 citations). Andrei Belitski has collaborated with scholars based in Germany, Italy and United Kingdom. Frequent co-authors include Nikos K. Logothetis, Stefano Panzeri, Cesare Magri, Yusuke Murayama, Arthur Gretton, Marcelo A. Montemurro, Peter Desain, Jason Farquhar, Christoph Kayser and Olivier Bousquet. Their work appears in journals such as Journal of Neural Engineering, Journal of Computational Neuroscience, Journal of Neuroscience, Magnetic Resonance Imaging and neural information processing systems.
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.