Taco Cohen Google Scholar: h-index, Total Citations, and Citation Map
Taco Cohen's h-index is 47 (87 i10-index, 20,126+ total citations across 170+ publications) according to Google Scholar as of November 2026. Taco Cohen is affiliated with Meta / FAIR.
Taco Cohen is a researcher affiliated with Meta / FAIR, specializing in Machine Learning. Their work has been cited 20,126 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Taco Cohen's Citation Metrics
Bibliometric impact based on 170 indexed publications.
- H-Index
- 47
- i10-Index
- 87
- Total Citations
- 20,126
- Citing Countries
- 41
As of November 2026.
Taco Cohen has an h-index of 47 and 20,126 total citations across 170 publications, with research cited by institutions in 41 countries.
Global Impact Map
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Group Equivariant Convolutional Networks
20163,602
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Taco Cohen's research
Taco Cohen is a researcher in Machine Learning at Meta / FAIR. Their work has been cited 20,126 times across 170 publications (h-index 47), according to Google Scholar.
Their most-cited work, “Group Equivariant Convolutional Networks” (2016), has accumulated 3,602 citations. Other influential works include “Geometric deep learning: Grids, groups, graphs, geodesics, and gauges” (2021) with 2,784 citations and “Spherical CNNs” (2018) with 1,609 citations.
Citations of Taco Cohen's research come primarily from United States, China and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
