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Topic · Computer Vision and Pattern Recognition

Graph Theory and Algorithms

Graph Theory and Algorithms is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 12k research works in it since 1955. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on graph matching, graph processing, and pattern recognition techniques using distributed computing and parallel algorithms. It covers topics such as subgraph isomorphism, large-scale graphs, graph analytics, and spectral techniques for graph analysis.

  • Graph Matching
  • Graph Processing
  • Pattern Recognition
  • Distributed Computing
  • Graph Analytics
  • Subgraph Isomorphism
  • Large-scale Graphs
  • Graph Database
  • Parallel Algorithms
  • Spectral Techniques
Research works
12k
fractional, since 1955
In the world top 10%
1.2k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+43%
the tick is no change
Largest producer
China
49% of the 10 largest, 2022-now
Graph Theory and Algorithms

Which countries lead Graph Theory and Algorithms research?

By volume, China and the United States publish the most (1.5k and 611 works in 2022-now).

By volume, 2022-now

  1. 1 China 1.5k works
  2. 2 United States 611 works
  3. 3 India 249 works
  4. 4 Germany 164 works
  5. 5 France 106 works
  6. 6 United Kingdom 92 works
  7. 7 Japan 89 works
  8. 8 South Korea 79 works
  9. 9 Australia 77 works
  10. 10 Italy 74 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 49.5%United States: 20.0%India: 8.2%Germany: 5.4%6 others listed: 16.9%49%largest
China1,508 · 49.5%United States611 · 20.0%India249 · 8.2%Germany164 · 5.4%6 others listed517 · 16.9%

Shares of the rows listed above, not of the whole node.

Which institutions lead Graph Theory and Algorithms research?

By volume in 2022-now, Chinese Academy of Sciences publishes the most Graph Theory and Algorithms research, followed by National University of Defense Technology and Tsinghua University.

By volume, 2022-now

  1. 1 Chinese Academy of SciencesChina 63 works
  2. 2 National University of Defense TechnologyChina 41 works
  3. 3 Tsinghua UniversityChina 39 works
  4. 4 Centre National de la Recherche ScientifiqueFrance 34 works
  5. 5 Shanghai Jiao Tong UniversityChina 30 works
  6. 6 Peking UniversityChina 28 works
  7. 7 Northeastern UniversityChina 26 works
  8. 8 Huazhong University of Science and TechnologyChina 26 works
  9. 9 University of Science and Technology of ChinaChina 24 works
  10. 10 Beijing Institute of TechnologyChina 23 works

Who are the leading researchers in Graph Theory and Algorithms?

The most-cited researchers publishing on Graph Theory and Algorithms include Yoshua Bengio, Yann LeCun and Li Fei-Fei.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Yann LeCun United States 256k citations
  3. 3 Li Fei-Fei United States 225k citations
  4. 4 Kai You Wang China 224k citations
  5. 5 Michael I. Jordan United States 182k citations
  6. 6 Oriol Vinyals United States 177k citations
  7. 7 Luc Van Gool Switzerland 177k citations
  8. 8 H. Vincent Poor United States 165k citations
  9. 9 Anil Kumar Jain United States 160k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Graph Theory and Algorithms?

The most cited paper in Graph Theory and Algorithms is "A Comprehensive Survey on Graph Neural Networks" (Zonghan Wu, Shirui Pan, Fengwen Chen et al., 2020), with 10,010 citations. Next come "The Graph Neural Network Model" (9,764) and "Graph neural networks: A review of methods and applications" (5,883).

Most cited papers
#PaperReleasedCitations
1 A Comprehensive Survey on Graph Neural Networks Zonghan Wu, Shirui Pan, Fengwen Chen et al. · IEEE Transactions on Neural Networks and Learning Systems Open access 24 Mar 2020 10,010
2 The Graph Neural Network Model Franco Scarselli, M. Gori, Ah Chung Tsoi et al. · IEEE Transactions on Neural Networks Open access 10 Dec 2008 9,764
3 Graph neural networks: A review of methods and applications Jie Zhou, Ganqu Cui, Shengding Hu et al. · AI Open Open access 2020 5,883
4 Introduction to Graph Theory J. Fields 2001 4,070
5 Geometric Deep Learning: Going beyond Euclidean data Michael M. Bronstein, Joan Bruna, Yann LeCun et al. · IEEE Signal Processing Magazine Open access Jul 2017 3,748
All 100 most cited papers, with filters and sorting

Where is Graph Theory and Algorithms research done?

The largest centres of Graph Theory and Algorithms research in 2022-now are Beijing (China), Shanghai (China), Changsha (China) and Wuhan (China). Among places with at least 20 works in it, it is an unusually large share of all research in Hong Kong, Changsha and Shenzhen.

Largest cities, 2022-now

  1. 1 BeijingChina 335 works
  2. 2 ShanghaiChina 111 works
  3. 3 ChangshaChina 77 works
  4. 4 WuhanChina 69 works
  5. 5 HangzhouChina 62 works
  6. 6 NanjingChina 59 works
  7. 7 Hong KongChina 58 works
  8. 8 GuangzhouChina 56 works
  9. 9 Xi'anChina 54 works
  10. 10 ShenzhenChina 52 works

Where it is the local speciality

  1. Hong KongCN · 58.2 works4.7×
  2. ChangshaCN · 77.5 works4.2×
  3. ShenzhenCN · 52.2 works4.1×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Graph Theory and Algorithms than the world average.

See Graph Theory and Algorithms on the map

Where is the best place to study Graph Theory and Algorithms?

Among universities, judged by research, Chinese University of Hong Kong, Hong Kong University of Science and Technology and Tsinghua University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 19.43%fractional works in this field (log) →share of work in the world top 10% →Chinese University o…Hong Kong University…Tsinghua UniversityPeking University
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Chinese University of Hong KongChina 82.429.3%7.3×18 +76.3%
2Hong Kong University of Science and TechnologyChina 81.727.0%12.5×17 +49.6%
3Tsinghua UniversityChina 76.922.2%5.1×39 +64.0%
4Peking UniversityChina 67.218.1%4.1×28 +80.3%
5National University of SingaporeSingapore 63.320.1%3.8×15 +67.5%
6Nanyang Technological UniversitySingapore 61.314.8%6.5×17 +53.9%
7Shanghai Jiao Tong UniversityChina 61.115.3%3.1×30 +81.5%
8National University of Defense TechnologyChina 60.311.2%16.2×41 +88.1%
9University of Science and Technology of ChinaChina 59.817.5%6.0×24 +247.7%
10University of Electronic Science and Technology of ChinaChina 59.218.8%5.8×22 +190.1%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Graph Theory and Algorithms, country by country

Is Graph Theory and Algorithms research growing?

Output in 2022-2025 was 43% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Graph Theory and Algorithms.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Graph Theory and Algorithms as a percentage of every work published that year, 0.015% in 2024.

still counting0.010%0.020%0.030%Graph Theory and Algorithms0.020% in 202519801990200020102020

Fractional works of Graph Theory and Algorithms over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Graph Theory and Algorithms9.8% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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