An Introduction to Variational Methods for Graphical Models
1999 • 5339 Citations
Published in Machine Learning
Tommi Jaakkola
Tommi Jaakkola is a researcher affiliated with MIT, specializing in AI & Machine Learning. Their work has been cited 76,691 times. This profile visualizes their global influence, highlighting strong citation networks in AU.
AI & Machine Learning
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Tommi Jaakkola's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 76,691
- Citing Countries
- 8
As of April 2026.
Tommi Jaakkola has an h-index of 1 and 76,691 total citations across 1 publication, with research cited by institutions in 8 countries.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
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Top Citing Countries(Limited)
Australia(AU)
9United Kingdom(GB)
4United States(US)
3China(CN)
2Canada(CA)
2United States(US)
1Singapore(SG)
1Italy(IT)
1Top Citing Institutions(Limited)
Deakin University
4Durham University
4Monash University
3The University of Texas at Austin
2Griffith University
1Ngee Ann Polytechnic
1Fondazione Bruno Kessler
1Chinese Academy of Sciences
1Twitter
1Google Research
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 8 of 8 countries (23 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
Linhao Luo
7.0Monash University
Australia· Cited your work 1 time
IndependentTop institution - #2
Yuan-Fang Li
7.0Monash University
Australia· Cited your work 1 time
IndependentTop institution - #3
Mingyuan Zhou
7.0The University of Texas at Austin
United States· Cited your work 1 time
IndependentTop institution - #4
Zhendong Wang
7.0The University of Texas at Austin
United States· Cited your work 1 time
IndependentTop institution - #5
Xiaochun Cao
7.0Chinese Academy of Sciences
China· Cited your work 1 time
IndependentTop institution - #6
Mohsen Ghavamzadeh
8.5Google Research
USA· Cited your work 1 time
IndependentTop institutionDiversifies geography - #7
Li Liu
7.0National University of Defense Technology
China· Cited your work 1 time
IndependentTop institution - #8
Sam Bond-Taylor
5.0Durham University
United Kingdom· Cited your work 1 time
Independent - #9
Chris G. Willcocks
5.0Durham University
United Kingdom· Cited your work 1 time
Independent - #10
Vladimir Makarenkov
6.5Université du Québec à Montréal
Canada· Cited your work 1 time
IndependentDiversifies 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 (AT&T). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
Paul Fieguth, Moloud Abdar, Farhad Pourpanah, Sadiq Hussain + 8 more
Information Fusion· cites “An Introduction to Variational Methods for Graphical Models”
Sam Bond-Taylor, Adam Leach, Yang Long, Chris G. Willcocks
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)· cites “An Introduction to Variational Methods for Graphical Models”
Shirui Pan, Linhao Luo, Yuan-Fang Li, Gholamreza Haffari
12th International Conference on Learning Representations (ICLR 2024)· cites “An Introduction to Variational Methods for Graphical Models”
Zhendong Wang, Jonathan J. Hunt, Mingyuan Zhou
ICLR 2023· cites “An Introduction to Variational Methods for Graphical Models”
· cites “An Introduction to Variational Methods for Graphical Models”
Top Cited Works(Showing 1 of 1)
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Citation Trend (Last 10 Years)
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