Overcoming catastrophic forgetting in neural networks
2017 • 12524 Citations
Published in Proceedings of the National Academy of Sciences (PNAS)
Raia Hadsell
Raia Hadsell is a researcher affiliated with Google DeepMind, specializing in AI & Machine Learning. Their work has been cited 59,026 times. This profile visualizes their global influence, highlighting strong citation networks in US.
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Raia Hadsell's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 59,026
- Citing Countries
- 2
As of April 2026.
Raia Hadsell has an h-index of 1 and 59,026 total citations across 1 publication, with research cited by institutions in 2 countries.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
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Top Citing Countries(Limited)
United States(US)
13United Kingdom(GB)
4Top Citing Institutions(Limited)
Northeastern University
5Massachusetts Institute of Technology
4University of Oxford
2California Institute of Technology
2Imperial College London
1Arizona State University
1University of California, Santa Cruz
1University of Cambridge
1Visa 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.
Citer Influence Network
Visa-ready visualisation: each outer ring node is a country citing this scholar. Node size & edge weight scale with citing-paper count. Showing top 2 of 2 countries (17 total citations).
Letter of Support — Candidate Recommenders
Ranked by EB-1A / O-1A relevance: independence from your home institution, affiliation with a top-ranked institution, repeat citations of your work, and recency. Reach out to the highest-scoring candidates to request support letters.
- #1
Ziming Liu
7.0Massachusetts Institute of Technology
United States· Cited your work 1 time
IndependentTop institution - #2
Marin Soljačić
7.0Massachusetts Institute of Technology
United States· Cited your work 1 time
IndependentTop institution - #3
Yarin Gal
8.5University of Oxford
UK· Cited your work 1 time
IndependentTop institutionDiversifies geography - #4
Ilia Shumailov
8.5University of Oxford
UK· Cited your work 1 time
IndependentTop institutionDiversifies geography - #5
Sachin Vaidya
7.0Massachusetts Institute of Technology
United States· Cited your work 1 time
IndependentTop institution - #6
Max Tegmark
7.0Massachusetts Institute of Technology
United States· Cited your work 1 time
IndependentTop institution - #7
Thomas Y. Hou
7.0California Institute of Technology
United States· Cited your work 1 time
IndependentTop institution - #8
Yixuan Wang
7.0California Institute of Technology
United States· Cited your work 1 time
IndependentTop institution - #9
Zakhar Shumaylov
8.5University of Cambridge
UK· Cited your work 1 time
IndependentTop institutionDiversifies geography - #10
Yiren Zhao
8.5Imperial College London
UK· Cited your work 1 time
IndependentTop institutionDiversifies geography
Scores combine 5 signals: independence (+3), prestige institution (+2), repeat citations (+2 per paper, cap 5), recent activity (+1), and geography diversity (+1.5). Identity matching uses name + institution; namesakes at the same org are merged.
Cited by 5 papers
5 / 5 independent
Citations flagged as non-independent share the scholar's home institution (DeepMind). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
· cites “Overcoming catastrophic forgetting in neural networks”
Zeyu Han, Chao Gao, Jinyang Liu, Jeff (Jun) Zhang + 1 more
Transactions on Machine Learning Research (TMLR)· cites “Overcoming catastrophic forgetting in neural networks”
Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle + 4 more
International Conference on Learning Representations (ICLR) 2025· cites “Overcoming catastrophic forgetting in neural networks”
Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Nicolas Papernot + 2 more
Nature· cites “Overcoming catastrophic forgetting in neural networks”
· cites “Overcoming catastrophic forgetting in neural networks”
Top Cited Works(Showing 1 of 1)
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Citation Trend (Last 10 Years)
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