Michael B. Cohen
- Cognitive Neuroscience top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Co-authors
- Stephen GrossbergYin Tat LeeZhao SongGeorge A. AlvarezTodd S. HorowitzCameron MuscoChristopher MuscoTalia Konkle
- Topics
- Face Recognition and Perception (10 papers)Visual perception and processing mechanisms (10 papers)Sparse and Compressive Sensing Techniques (9 papers)
- Partner nations
- United StatesIsraelGermany
In The Last Decade
Michael B. Cohen
69 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 159
- Cognitive Neuroscience 659
- Artificial Intelligence 336
- Computer Vision and Pattern Recognition 225
- Computational Theory and Mathematics 188
- Molecular Biology 166
Countries citing papers authored by Michael B. Cohen
This map shows the geographic impact of Michael B. Cohen'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 Michael B. Cohen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael B. Cohen more than expected).
Fields of papers citing papers by Michael B. Cohen
This network shows the impact of papers produced by Michael B. Cohen. 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 Michael B. Cohen. The network helps show where Michael B. Cohen may publish in the future.
Co-authorship network of co-authors of Michael B. Cohen
This figure shows the co-authorship network connecting the top 25 collaborators of Michael B. Cohen. A scholar is included among the top collaborators of Michael B. Cohen 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 Michael B. Cohen. Michael B. Cohen 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 | 6 | |
| 3 | 24 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | On Acceleration with Noise-Corrupted Gradients | 5 |
| 7 | 18 | |
| 8 | Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More | 21 |
| 9 | 15 | |
| 10 | 46 | |
| 11 | 70 | |
| 12 | 1 | |
| 13 | 52 | |
| 14 | 11 | |
| 15 | 24 | |
| 16 | 64 | |
| 17 | 30 | |
| 18 | 48 | |
| 19 | 57 | |
| 20 | 89 |
About Michael B. Cohen
Michael B. Cohen is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Cognitive Neuroscience, having authored 70 papers that have together received 1.9k indexed citations. Recurring topics across this work include Face Recognition and Perception (10 papers), Visual perception and processing mechanisms (10 papers) and Sparse and Compressive Sensing Techniques (9 papers). The work is most often cited by research in Computational Mathematics (25 citations), Cognitive Neuroscience (659 citations) and Computational Theory and Mathematics (188 citations). Michael B. Cohen has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Stephen Grossberg, Yin Tat Lee, Zhao Song, George A. Alvarez, Todd S. Horowitz, Cameron Musco, Christopher Musco, Talia Konkle, Richard Peng and David W. Murhammer. Their work appears in journals such as Proceedings of the National Academy of Sciences, NeuroImage and Cancer.
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.