Jeff Clune: h-index, Total Citations, and Citation Map
Jeff Clune's h-index is 65 (110 i10-index, 48,299+ total citations across 142+ publications) according to Google Scholar as of July 2026. Jeff Clune is affiliated with Professor, Computer Science,U British Columbia; CIFAR AI Chair, Vector Institute.
Jeff Clune is a researcher affiliated with Professor, Computer Science,U British Columbia; CIFAR AI Chair, Vector Institute, specializing in various fields. Their work has been cited 48,299 times. This profile visualizes their global influence, spanning a global audience.
Jeff Clune's Citation Metrics
Bibliometric impact based on 142 indexed publications.
- H-Index
- 65
- i10-Index
- 110
- Total Citations
- 48,299
- Citing Countries
- 0
As of July 2026.
Jeff Clune has an h-index of 65 and 48,299 total citations across 142 publications, with research cited by institutions in 0 countries.
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How transferable are features in deep neural networks?
201413,641
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Citation Trend (Last 10 Years)
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About Jeff Clune's research
Jeff Clune is a researcher at Professor, Computer Science,U British Columbia; CIFAR AI Chair, Vector Institute. Their work has been cited 48,299 times across 142 publications (h-index 65), according to Google Scholar.
Their most-cited work, “How transferable are features in deep neural networks?” (2014), has accumulated 13,641 citations. Other influential works include “Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images” (2015) with 5,019 citations and “How transferable are features in deep neural networks?” (2014) with 3,456 citations.
