Rémi Munos Google Scholar: h-index, Total Citations, and Citation Map
Rémi Munos's h-index is 1 (1 i10-index, 56,436+ total citations across 1+ publications) according to Google Scholar as of October 2026. Rémi Munos is affiliated with FAIR, Meta.
Rémi Munos is a researcher affiliated with FAIR, Meta, specializing in AI & Machine Learning. Their work has been cited 56,436 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Rémi Munos's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 56,436
- Citing Countries
- 5
As of October 2026.
Rémi Munos has an h-index of 1 and 56,436 total citations across 1 publication, with research cited by institutions in 5 countries.
Global Impact Map
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Bootstrap your own latent-a new approach to self-supervised learning
202010,487
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 Rémi Munos's research
Rémi Munos is a researcher in AI & Machine Learning at FAIR, Meta. Their work has been cited 56,436 times across 1 publications, according to Google Scholar.
Their most-cited work, “Bootstrap your own latent-a new approach to self-supervised learning” (2020), has accumulated 10,487 citations.
Citations of Rémi Munos's research come primarily from United States, Australia and China, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
